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google-plus一首英文歌，里面有段渐强的，歌词有很多i know you_百度知道
一首英文歌，里面有段渐强的，歌词有很多i know you
很激昂 是i know
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air supply-
Making love out of nothing at all
是吗？歌词如下：I know just how to whisper, and I
I know just where and I know just how to lie. I know just how to fake it, and I kno I know just when to face the truth, and then I know just when to dream. And I know just where to touch you, and I kno I know when to pull you closer, and I know when to let you loose. And I know the night is fading, and I know that time' and I'm never gonna tell you everythingI've got to tell you, but I know I've got to give it a try. And I know the roads to riches, and I k I know all the rulesand then I know how to break 'em and I always know the name of the game. But I don't know how to leave you, and I'l and I don't know how you do it, making love out of nothing at all(Making love) out of nothing at all, (making love) out of nothing at all, (making love) out of nothing at all, (making love) out of nothing at all, (making love) out of nothing at all(making love) out of nothing at all. Every time I see you all the rays of the sun are streaming through th and every star in the sky is taking aim at your eyes like a spotlight, The beating of my heart is a drum, and it's lost and it's looking for a rhythm like you. You can take the darkness from the pit of the nightand turn into a beacon burning endlessly bright. I've got to follow it, 'cause everything I know, well it's nothing till I give it to you. I can make the runner stumble, I can
And I can make every tackle, at the sound of the whistle, I can make all the stadiums rock. I can make tonight forever, Or I can make it d And I can make you every promise that has ever been made, And I can make all your demons be gone. But I'm never gonna make it without you, Do you really want to see me crawl? And I'm never gonna make it like you do, Making love out of nothing at all. (Making love) out of nothing at all(making love) out of nothing at all(making love) out of nothing at all(making love) out of nothing at all(making love) out of nothing at all(making love) out of nothing at all(making love)
采纳率：23%
希望能帮到你！You know what I want wantI know what you want wantTell me what I want wantI'll tell you what you want wantYou know what I want wantI know what you want wantTell me what I want wantI'll tell you what you want wantSo many ladies in the rooom (in the rooom)All that I can see is you (see is you)This dime piece is in this plaace (plaace)But you came through and took the case (whoooh)Cause I know what I likeAnd I know what I wantAnd I know how to get itLet me in your world (yeeaah)Yes I know what I likeAnd I know what I want (want)And I know how to get itLet me prove it to you one on oneCan I take you home girl (can I take you home girl)Get you all alone girl (get you all alone girl)And do you like I want to (aayyeah)Kiss you like I want to (kiss it like I want to)Can I take you home girlGet you all alone girl (get you all alone girl)And do you like I want toKiss you like I want to(And love you like I want to)I'm staring at you eye to eye (eye to eye)I'm nothin like these other guys (other guys)Let me drop this on yo mind (on yo mind)I'm not here to waste your timeCause I know what I like (I know what I)And I know what I want (I know what I)And I know how to get itLet me in your world (whooohh)Yes I know what I likeAnd I know what I want (what I want)And I know how to get it
不是···
如果你能多提供点信息
我会再帮你找
不然的话只能说抱歉了
希望能帮到你！
是一个女的唱的
[Do You Wanna]其中歌词是Do you wanna do you wannaDo you wanna make love to meI know you wanna I know you wannaI know you wanna make love to meI came to tell you that you re my favourite girlWould you like it if I put you into my world
是不h是Kelly Clarkson--Already Gone 歌词： remember all the things we wanted 我们想要记得过去的一r切5 now all our memories, they're haunted 可现在我们所有的记忆3都缠绕在心1头 we were always meant to say goodbye 这意味着我们该分0手2了h even with our fists held high 尽管我们拳头高举 it never would've worked out right 但也n不q能正确的解决问题 we were never meant for do or die 这也o不m意味着我们会这样分8开w i didn't want us to burn out 我不x想我们就这样燃尽 i didn't 。e here to hold you 我不m能过来保护你 now i can't stop 现在我也l该停止2了s i want you to know that it doesn't matter 我想让你知道。这并无h大s碍 where we take this road 不q管我们走哪条路 someone's gotta go 总有人o会离开n and i want you to know 可我又a想让你知道 you couldn't have loved me better 你不p能更好的爱我 but i want you to move on 但我又t想让你在这条路上g继续前行 so i'm already gone 所以7我选择离开u looking at you makes it harder 看着你困难前行 but i know that you'll find another 但我知道你会找到令一u个s伴侣 that doesn't always make you want to cry （如此困难）都未曾让你哭泣 started with a perfect kiss 以6一q个h完美的吻开c始（恋爱） then we could feel the poison set in 然后我们感觉到毒药慢慢侵袭而来 perfect couldn't keep this love alive 完美的一j切4却并不u能使这种爱继续存在 you know that i love you so 你知道我是如此爱你 i love you enough to let you go 我爱你已x经到放你走的地步 i want you to know that it doesn't matter 我想让你知道。这并无l大y碍 where we take this road 不e管我们走哪条路 someone's gotta go 总有人t会离开d and i want you to know 可我又s想让你知道 you couldn't have loved me better 你不i能更好的爱我 but i want you to move on 但我又u想让你在这条路上q继续前行 so i'm already gone 所以8我选择离开k i'm already gone, already gone 我已i经离开w，已h经离开i了v。。。 you can't make it feel right 你肯定会不y适应 when you know that it's wrong 但当你发现哪里不j适应的时候 i'm already gone, already gone 我已n经离开w,已c经离开r了m。。。 there's no moving on 前方4已l经没有路了w so i'm already gone 所以3我选择离开h remember all the things we wanted 我们想要记得过去的一x切7 now all our memories, they're haunted 可现在我们所有的记忆5都缠绕在心2头 we were always meant to say goodbye 这意味着我们该分5手1了q i want you to know that it doesn't matter 我想让你知道。这并无m大b碍 where we take this road 不f管我们走哪条路 someone's gotta go 总有人h会离开u and i want you to know 可我又q想让你知道 you couldn't have loved me better 你不h能更好的爱我 but i want you to move on 但我又k想让你在这条路上v继续前行 so i'm already gone 所以0我选择离开n i'm already gone, already gone 我已n经离开w,已o经离开g了r you can't make it feel right 你肯定会觉得不w适应 when you know that it's wrong 但当你明白哪里不l适应的时候 i'm already gone, already gone 我已l经离开w, 已m经离开v了q there's no moving on 前方5已i经没有路了h so i'm already gone 所以6我选择离开o
jホy▄vゥvゥnc悚fモヌ】fモヌ】c悚l哀
i know you want me.是不是？
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Jay-Z.听听看。and i know 萧亚轩。
Maroon 5-Moves Like Jagger
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我们会通过消息、邮箱等方式尽快将举报结果通知您。From hysterical psychosis to Reactive Dissociative Psychosis | SpringerLink
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From hysterical psychosis to Reactive Dissociative PsychosisOnno van der HartEliezer WitztumBarbara FriedmanArticle
In this paper Reactive Dissociative Psychosis (RDP) is seen as a post-traumatic stress response and as a subcategory of Brief Reactive Psychosis (BRP). A review of the literature and the evolution of RDP from Hysteria and Hysterical Psychosis are given. Issue is taken with defining the duration of BRP as “Brief.” The authors argue that long-standing psychotic symptoms may be traumatically induced. The dissociative aspects of RDP as its key feature and the concomitant implications for accurate diagnosis are proposed. The usefulness of applying hypnosis in RDP treatment is summarized in a case study from Janet and detailed in a case from the authors' practice.hysterical psychosis reactive dissociative psychosis brief reactive psychosis posttraumatic stress dissociation traumatic grief hypnotherapy This is a preview of subscription content,
to check access.Unable to display preview.&Aikins, H.A. (1923). Casting out a ‘stuttering devil.’J. Abnorm. Social Psychol. 18: 137–152. In Murphy G. (ed.),An Outline of Abnormal Psychology, The Modern Library, New York, 1929, pp. 175–192.American Psychiatric Association (1968).DSM-III Washington, DC: Author.American Psychiatric Association (1987).DSM-III-R Washington, DC: Author.Babinksi, J. (1901). Définition de l'hystérie.Rev. Neurol. 9: .Babinski, J. (1909). Démembrement de l'hystérie traditionelle. Pithiathismc.La Semaine Médicale. 59(1): 3–8.Barkin, R., Braun, B. G., and Kluft, R. P. (1986). The dilemma of drug treatment for multiple personality disorder. In Braun, B. G. (ed.),Treatment of Multiple Personality Disorder Washington, DC: American Psychiatric Press, pp. 109–132.Bleuler, E. (1911). Dementia praecox oder Gruppe der Schizophrenien. In Aschaffenburg, G. (ed.),Handbuch der Psychiatrie spezieller Teil 4 Abt. I. Vienna: F. Deuticke.Bleuler, E. (1950).Dementia Praecox or the group of schizophrenias. International Universities Press, Madison.Bilu, Y., and Abramovich, H. (1985). In search of the Saddiq: Visitational dreams among Moroccan Jews in Israel.Psychiatry 38: 145–159.Bilu, Y., Witztum, E., and Van der Hart, O. (1989). Paradise regained: ‘Miraculous healing’ in an Israeli psychiatric clinic.Cult. Med. Psychiatry 14, 105–127.Breuer, J., and Freud, S. (1893/95). On the psychical mechanism of hysterical phenomena: A preliminary communication. In Strachey, J. (Transl. and Ed.),The Standard Edition of the Complete Psychological Works of Sigmund Freud, Vol. 3. London: Hogarth Press, 1955, pp. 53–69.Breuer, J. (1895). Theoretical. In Strachey, J. (Transl. and Ed.),The standard Edition of the Complete Psychological Works of Sigmund Freud, Vol. 3. Hogarth Press, London, 1955, pp. 259–333.Breukink, H. (1923). Over de behandeling van sommige psychosen door middel van een bijzondere vorm der kathartisch-hypnotische methode.Tijdschrift voor Geneeskunde 67: .Carrot, E., Charlin, A., and Remond, A. (1945). L'hystéro-catatonie.Annal. Méd. Psychol. 103: I, 347–353.Claude, H. (1937). Rapport de l'hystérie avec la schizophrénie.Annal. Méd. Psychol. 95: II, 1–14, 141–164 (Discussion).Courbon, P. (1937). Hystérie, schizophrénie, pithiatisme et simulation.Annal. Méd. Psychol. 95: II, 257–268.Dow, J. (1986). Universal aspects of symbolic healing: A theoretical analysis.Am Anthropol. 7: 333–375.Fernandez, J. W. (1977). The performance of ritual metaphor. In Sapir, J. D. and Crocker, J. C. (eds.),The Social Use of Metaphor University of Pennsylvania Press, Philadelphia, pp. 100–131.Follin, S., Chazaud, J., and Pilon, L. (1961). Cas cliniques de psychoses hystériques.Evol. Psychiatr. 26: 257–286.Friedman, B. (1989). Post-traumatic stress disorder and dissociation, response versus disorder. Paper presented at the Second Annual Conference on Multiple Personality and Dissociation. Costa Mesa, California.Hirsch, S. J., and Hollender, M. H. (1969). Hysterical psychosis: Clarification of a concept.Am. J. Psychiatry 125: 81–87.Hock, A. (1868).Eenvoudige mededelingen aangaande de genezing van eene krankzinnige door het levens-magnetismus. s Gravenhage: De Gebroeders van Cleef.Hollender, M. H. and Hirsch, S. J. (164). Hysterical psychosis.Am. J. Psychiatry 120: .Hugenholz, P. Th. (1946). Kliniek der psychogene psychosen. In van der Horst L. (ed.),Anthropologische psychiatrie, Deel II: Randpsychosen Van Holkema & Warendorf, Amsterdam, pp. 415–478.Janet, P. (1889).Automatisme psychologique Félix Alcan, Paris. Reprint: Société Pierre Janet, Paris, 1974.Janet, P. (1893).Contribution á l'étude des accidents mentaux chez les hystériques. Thèse médicale. Paris: Reuff & Cie. Also in: P. Janet (1911),L'Etat mental des hystériques (second edition), Félix Alcan, Paris. Reprint: Lafitte Reprint, Marseille, 1984.Janet, P. (1894). Histoire d'une idée Fixe.Rev. Philos. 37: 121–168. Also in: P. Janet (1898),Névroses et idées fixes, Vol. 1. Paris: Félix Alcan, pp. 156–212.Janet, P. (1894/5). Un cas de possession et l'exorcisme moderne.Bulletin de l'Université de Lyon, Dec. 1894–Jan. . Also in: P. Janet (1898).Névroses et idées fixes, Vol. 1, Paris: Félix Alcan, pp. 375–406.Janet, P. (1898).Névroses et idées fixes, Vol. 1. Paris: Félix Alcan. (a)Janet, P. (1898). Traitement psychologique de l'hystérie. In Robin, A. (ed.),Traité de thérapeutique appliquée. Paris: Rueff. (b) Also in: P. Janet (1911),L'Etat mental des hystériques, sec. ed. Paris: Félix Alcan.Janet, P. (1901).The Mental State of Hystericals Putnam & Sons, New York. Reprint: University Publications of America, Washington, DC, 1977.Janet, P. (1903).Les obsessions et la psychasthénie. Félix Alcan, Paris. Reprint: Arno Press, New York, 1976.Janet, P. (1904). L'Amnésie et la dissociation des sourenirs par l'émotion.J. Psychol. 1: 417–453.Janet, P. (1911).L'Etat mental des hystériques (second edition), Félix Alcan, Paris. Reprint: Lafitte Reprints, Marseille, 1984.Janet, P. (1928).De l'angoisse à l'extase, Vol. 2:Les sentiments fondamentaux. Félix Alcan, Paris. New edition: Société Pierre Janet, Paris, 1975.Jauch, A. D., and Carpenter, W. T. (1988). Reactive psychosis, I.J. Nerv. Mental Dis. 176: 72–81. (a).Jauch, A. D., and Carpenter, W. T. (1988). Reactive psychosis, IIJ. Nerv. Ment. Dis. 176: 82–86. (b)Klein, D. F., Gittelman, R., Quitkin, F., and Rifkin, F. (1980).Diagnosis and Drug Treatment of Psychiatric Disorders: Adult and Children. Williams & Wilkins, Baltimore.Langness, I. (1976). Hysterical psychoses and possessions. In Lebra, W. P. (ed.),Culture-Bound Syndromes, Ethnopsychiatry, and Alternate Therapies The University Press of Hawaii, Honolulu, pp. 56–67.Mairet, A., and Salager, E. (1910).La folie hystérique Coulet et Fils, Montpellier.Malcval, J. M. (1981).Folies hystériques et psychoses dissociatives Payot, Paris.Mallett, B. L., and Gold, S. (1964). A pseudo-schizophrenic hysterical syndrome.Brit. J. Med. Psychol. 37: 59–70.Martin, P. A. (1971). Dynamic considerations in the hysterical psychosis.Am. J. Psychiat. 128: 101–104.Moreau de Tours, J. J. (1845).Du hachisch et de l'aliénation mentale. Paris: Librairie de Fortin, Masson et Cie. English edition:Hashish and mental illness. Raven Press, New York, 1973.Moreau de Tours, J. J. (1855). De l'identité de l'état de rêve et de la folie.Annal. Méd. Psychol. 3e serie, I, 361–408.Moreau de Tours, J. J. (1865).De la folie hystérique et de quelques phénomenes nerveux propres à l'hystérie convulsive, a l'hystéro-épilepsie et à l'épilepsie Masson, Paris.Moreau de Tours, J. J. (1869).Traité pratique de la folie névropathique (vulgo hystérique) Germer Baillière, Paris.Nemiah, J. C. (1974). Conversion: Fact or chimera?J. Psychiatry Med. 5: 443–448.Pankow, G. W. (1974). The body image in hysterical psychosis.Int. J. Psychoanal. 55: 407–414.Prinquet, G. (1977). A propos d'un cas de psychose hystérique.Nouv. Press. Méd. 6: 441–443.Putnam, F. (1985). Dissociation as a response to extreme trauma. In Kluft, R. P. (ed.),Childhood Antecedents of Multiple Personality American Psychiatric Press, Washington, DC, pp. 65–97.Putnam, F. (1989). Pierre Janet and modern views of dissociation.J. Traum. Stress 2: 413–429.Raecke (1915). Ueber hysterische und katatonische Situationspsychosen.Arch. Psychiatr. Nervenkr. 55: 771–780.Regis, E. (1906).Précis de psychiatrie (third edition), Octave Doin, Paris.Richman, J., and White, H. (1970). A family view of hysterical psychosis.Am. J. Psychiatry 127: 280–285.Rosenbaum, M. (1980). The role of the term schizophrenia in the decline of diagnosis of multiple personality.Am. J. Psychiatry 37: .Siomopoulos, V. (1971). Hysterical psychosis: Psychopathological aspects.Brit. J. Med. Psychol. 44: 95–100.Spiegel, D. (1986). Dissociating damage.Am. J. Clin. Hypn. 29: 123–131.Spiegel, D. (1988). Dissociation and hypnosis in post-traumatic stress disorders.J. Traum. Stress 1: 3–16.Spiegel, D., and Carde?a, E. (1990). New use of hypnosis in the treatment of posttraumatic stress disorder.J. Clin. Psychiatry 51 (Suppl.): 39–43.Spiegel, D., and Fink, R. (1979). Hysterical psychosis and hypnotizability.Am. J. Psychiatry 136: 777–781.Spiegel, D., Hunt, T., and Dondershine, H. E. (1988). Dissociation and hypnotizability in posttraumatic stress disorder.Am. J. Psychiatry 145: 301–305.Steingard, S., and Frankel, F. H. (1985). Dissociation and psychotic symptoms.Am. J. Psychiatry 142: 953–955.Van der Hart, O. (1983).Rituals in Psychotherapy Irvington, New York.Van der Hart (1986). Metaphoric and symbolic imagery in the hypnotic treatment of an urge to wander.Austr. J. Clin. Exp. Hypn. 13: 83–95.Van der Hart, O., Brown, P., and Turco, R. N. (1990). Hypnotherapy for traumatic grief: Janetian and modern approaches integrated.Am. J. Clin. Hypn. 32: 263–271.Van der Hart, O., Brown, P., and Van der Kolk, B. A. (1989). Pierre Janet's psychological treatment of posttraumatic stress.J. Traum. Stress 2: 379–395.Van der Hart, O., and Friedman, B. (1989). A reader's guide to Pierre Janet on dissociation: A neglected intellectual heritage.Dissociation 2(1): 3–16.Van der Hart, O., and Horst, R. (1988). The dissociation theory of Pierre Janet.J. Traum. Stress 2: 397–412.Van der Hart, O., and Van der Velden, K. (1987). The hypnotherapy of Dr. Andries Hoek: Uncovering hypnotherapy before Janet, Breuer, and Freud.Am. J. Clin. Hypn. 29: 264–271.Van der Kolk, B. A., Brown, P. and Van der Hart, O. (1989). Pierre Janet on post-traumatic stress.J. Traum. Stress 2: 365–378.Villechenoux, C. (1968).Le cadre de la folie hystérique de 1870 à 1918. Thèse pour le doctorat en médecine. Paris: Faculté de Médecine de Paris.Waldfogel, S., and Butler, K. T. (1988). Another case of chronic PTSD with auditory hallucinations (Letter).Am. J. Psychiatry 145: 1314.Wing, J. K., Cooper, J. E., and Sartorius, N. (1974).The measurement and classification of psychiatric symptoms Cambridge University Press, Cambridge.Witztum, E., Van der Hart, O., and Friedman, B. (1988). The use of metaphor in psychotherapy.J. Contemp. Psychother. 18: 270–290.Witztum, E., and Van der Hart, O. (1992). Possession and persecution by demons: Cultural and dissociative views. In Goodwin, J. M. (ed.),Rediscovering trauma: Historical casebook and clinical applications. American Psychiatric Press, Washington, DC.Onno van der Hart1Eliezer Witztum2Barbara Friedman31.Regional Institute for Ambulatory Mental Health Care, Amsterdam South/New WestAmsterdamThe Netherlands2.Jerusalem Mental Health Center—Ezrath NashimJerusalemIsrael3.Dissociative Disorders InstituteLos AngelesWe’re releasing .
Each of the three major operating systems provides a native firewall, capable of blocking incoming and outgoing access when configured. However, the interface for each of these three firewall systems are dissimilar and each requires different methods of configuration. Furthermore, there are few options for cross-platform fleet configuration, and nearly all are commercial and proprietary.
In partnership with Airbnb, we have created a cross-platform firewall management extension for osquery. The extension enables programmatic control over the native firewalls and provides a common interface for each host operating system, permitting more advanced control over an enterprise fleet’s endpoint protections as well as closing the loop between endpoint monitoring and endpoint management.
Along with our , this extension shows the utility of . Programmatic control over endpoint firewalls means that an administrator can react more quickly to prevent the spread of malware on their fleet, prevent unexpected data egress from particularly vital systems, or block incoming connections from known malicious addresses. This is a huge advance in osquery’s capabilities, shifting it from merely a monitoring tool into both prevention and recovery domains.
What it can do now
The extension creates two new tables: HostBlacklist and PortBlacklist. These virtual tables generate their entries via the underlying operating systems’ native firewall interfaces: iptables on Linux, netsh on Windows, and pfctl on MacOS. This keeps them compatible with the widest possible range of deployments and avoids further dependence on external libraries or applications. It will work with your existing configuration, and, regardless of underlying platform, provide the same interface and capabilities.
Use osquery to access the local firewall configuration on Mac, Windows, and Linux
What’s on the horizon
While the ability to read the state of the firewall is useful, it’s the possibility of controlling them that we’re most excited about. With writable tables available in osquery, blacklisting a port or a host on a managed system will become as simple as an INSERT statement. No need to deploy an additional firewall management service. No more reviewing how you configure the firewall on macOS. Just write an INSERT statement and push it out the fleet.
Instantly block hostnames and ports across your entire fleet with osquery
Give it a try
With this extension you can query the state of blacklisted ports and hosts across a managed fleet and ensure that they’re all configured to your specifications. With the advent of the writable tables feature osquery can shift from a monitoring role to a management and preventative tool. This extension takes the first step in that direction.
We’re adding this extension to our managed . We’re committed to maintaining and extending our collection of extensions. You should check in and see what else we’ve released.
Do you have an idea for an osquery extension? File an issue on our GitHub repo for it.
for osquery development.
We’re releasing
without the need for a separate sync server.
is an application whitelist and blacklist system for macOS ideal for deployment across managed fleets. It uses a sync server from which daemons pull rules onto managed computers. However, the sync server provides no functionality for the bulk collection of logs or configuration states. It does not indicate whether all the agents have pulled the latest rules or how often those agents block execution of blacklisted binaries.
In partnership with Palantir, we have integrated Santa into the osquery interface as an extension. Santa can now be managed directly through osquery and no longer requires a separate sync server. Enterprises can use a single interface, osquery, to centrally manage logs and update or review agent configuration.
We’ve described writable access to endpoints as a . This extension shows why. Now, it’s possible to add remote management features to the osquery agent, which is normally limited to read-only access. This represents a huge advance in osquery’s capabilities, moving it from the role of strictly monitoring into an active and preventative role. Trail of Bits is pleased to announce the release of the Santa extension into our open-source repository of osquery extensions.
What it can do
Santa gives you fine-grained control over which applications may run on your computer. Add osquery and this extension into the mix, and now you’ve got fine-grained control over which applications may run on your fleet. Lock down endpoints to only run applications signed by a handful of approved certificates, or blacklist known malicious applications before they get a chance to run.
The extension can be loaded at the startup of osquery with the extension command line argument, e.g., osqueryi --extension path/to/santa.ext. On loading, it adds two new tables to the database: santa_rules and santa_events.The tables themselves are straightforward.
santa_rules consists of the three text columns: shasum, state, and type. The type column contains the rule type and may be either certificate or binary. state is either whitelist or blacklist. shasum contains either the hash of the binary or the signing certificate’s hash, depending on rule type.
The santa_events table has four text columns: timestamp, path, shasum, and reason. timestamp marks the time the deny event was logged. path lists the path to the denied application. shasum displays the hash of the file. reason shows the type of rule that caused the deny (either binary or certificate).
Time to use it
This extension provides a simplified interface to oversee and control your Santa deployment across your fleet, granting easy access to both rules and events. You can find it and other osquery extensions in our
of . We’ll continue to add new extensions. Take a look and see what we have available.
Hire us to tailor osquery to your needs
Do you have an idea for an osquery extension? File an issue on our
for osquery development.
Note: This feature depends on
which has not yet been merged.
if you’d like to try this feature now — we create custom binary builds to test upcoming features of osquery for our clients.
We’re releasing . It’s one more tool for incident response and data collection. But it’s also an opportunity to dispense with forensics toolkits and commercial services that offer similar capabilities.
Until now, osquery has been inadequate for performing the kind of filesystem forensics that is often part of an incident response effort. It collects some information about files on its host platforms – timestamps, permissions, owner and more – but anyone with experience in forensics will tell you that there’s a lot more data available on a file system if you’re willing to dig. Think additional timestamps, unallocated metadata, or stale directory entries.
The alternatives are often closed source and expensive. They become one more item in your budget, deployment roadmap, and maintenance schedule. And none of them integrate with osquery. You have to go to the extra effort of mapping the forensic report back to your fleet.
That changes today. In partnership with , we have integrated NTFS forensic information into the osquery interface as an extension. Consider this the first step toward a better, cost-effective, more efficient alternative that’s easier to deploy.
What it can do
The NTFS forensics extension provides specific additional file metadata from NTFS images, including filename timestamp entries, the security descriptor for files, whether a file has
(ADS), as well as other information. It also provides index entries for directory indices, including entries that are deallocated. You can find the malware that just cleaned up after itself, or altered its file timestamps but forgot about the filename timestamps, or installed a rootkit in the ADS of calc.exe, all without ever leaving osquery.
How to use it
Load the extension at the startup of osquery with the command line argument, e.g., &code&osqueryi.exe --extension path\to\ntfs_forensics.ext.exe&/code&. On loading, three new tables will be added to the database: ntfs_part_data, ntfs_file_data, and ntfs_indx_data.
ntfs_part_data
This table provides information about partitions on a disk image. If queried without a specified disk image, it will attempt to interrogate the physical drives of the host system by walking up from \\.\PhysicalDrive0 until it finds a drive number it fails to open.
Enumerating partition entries in an NTFS image
ntfs_file_data
This table provides information about file entries in an NTFS file system. The device and partition columns must be specified explicitly in the WHERE clause to query the table. If the path or inode column is specified, then a single row about the specified file is returned. If the directory column is specified, then a row is returned for every file in that directory. If nothing is specified, a walk of the entire partition is performed. Because the walk of the entire partition is costly, results are cached to be reused without reperforming the entire walk. If you need fresh results of a partition walk, use the hidden column from_cache in the WHERE clause to force the collection of live data (e.g., select * from ntfs_file_data where device=”\\.\PhysicalDrive0” and partition=2 and from_cache=0;).
Displaying collected data on a single entry in an NTFS file system
ntfs_indx_data
This table provides the content of index entries for a specified directory, including index entries discovered in slack space. Like ntfs_file_data, the device and partition columns must be specified in the WHERE clause of a query, as well as either parent_path or parent_inode. Entries discovered in slack space will have a non-zero value in the slack column.
Displaying inode entries recovered from a directory index’s slack space
Getting Started
This extension offers a fast and convenient way to perform filesystem forensics on Windows endpoints as a part of an incident response. You can find it and our other osquery extensions in our . We’re committed to maintaining and extending our collection of extensions. Take a look, and see what else we have available.
Hire us to tailor osquery to your needs
Do you have an idea for an osquery extension? File an issue on our GitHub repo for it.
for osquery development.
is a powerful technique for verifying arbitrary properties of a program via execution on a large set of inputs, typically generated stochastically.
is a library and executable I’ve been working on for applying property-based testing to EVM code (particularly code written in Solidity).
Echidna is a library for generating random sequences of calls against a given smart contract’s ABI and making sure that their evaluation preserves some user-defined invariants (e.g.: the balance in this wallet must never go down). If you’re from a more conventional security background, you can think of it as a fuzzer, with the caveat that it looks for user-specified logic bugs rather than crashes (as programs written for the EVM don’t “crash” in any conventional way).
The property-based testing functionality in Echidna is implemented with , a property-based testing library by Jacob Stanley. Think of Hedgehog as a nicer version of . It’s an extremely powerful library, providing automatic minimal testcase generation (“shrinking”), well-designed abstractions for things like , and most importantly for this blog post, abstract state machine testing tools.
After reading a particularly excellent blog post by Tim Humphries ( which I’ll refer to as the “Hedgehog post” from now on) about testing a simple state machine with this functionality, I was curious if the same techniques could be extended to the EVM. Many contracts I see in the wild are just implementations of some textbook state machine, and the ability to write tests against that invariant-rich representation would be invaluable.
The rest of this blog post assumes at least a degree of familiarity with Hedgehog’s state machine testing functionality. If you’re unfamiliar with the software, I’d recommend reading Humphries’s blog post first. It’s also worth noting that the below code demonstrates advanced usage of Echidna’s API, and you can also use it to test code .
First, we’ll describe our state machine’s states, then its transitions, and once we’ve done that we’ll use it to actually find some bugs in contracts implementing it. If you’d like to follow along on your own, all the Haskell code is in
and all the Solidity code is in .
Step 0: Build the model
Fig. 1: A turnstile state machine
The state machine in the Hedgehog post is a turnstile with two states (locked and unlocked) and two actions (inserting a coin and pushing the turnstile), with “locked” as its initial state. We can copy this code verbatim.
data ModelState (v :: * -& *) = TLocked
| TUnlocked
deriving (Eq, Ord, Show)
initialState :: ModelState v
initialState = TLocked
However, in the Hedgehog post the effectful implementation of this abstract model was a mutable variable that required I/O to access. We can instead use a simple Solidity program.
contract Turnstile {
bool private locked = // initial state is locked
function coin() {
function push() returns (bool) {
if (locked) {
return(false);
return(true);
At this point, we have an abstract model that just describes the states, not the transitions, and some Solidity code we claim implements a state machine. In order to test it, we still have to describe this machine’s transitions and invariants.
Step 1: Write some commands
To write these tests, we need to make explicit how we can execute the implementation of our model. The examples given in the Hedgehog post work in any MonadIO, as they deal with IORefs. However, since EVM execution is deterministic, we can work instead in any MonadState VM.
The simplest command is inserting a coin. This should always result in the turnstile being unlocked.
s_coin :: (Monad n, MonadTest m, MonadState VM m) =& Command n m ModelState
s_coin = Command (\_ -& Just $ pure Coin)
-- Regardless of initial state, we can always insert a coin
(\Coin -& cleanUp && execCall (&coin&, []))
-- Inserting a coin is just calling coin() in the contract
-- We need cleanUp to chain multiple calls together
[ Update $ \_ Coin _ -& TUnlocked
-- Inserting a coin sets the state to unlocked
, Ensure $ \_ s Coin _ -& s === TUnlocked
-- After inserting a coin, the state should be unlocked
Since the push function in our implementation returns a boolean value we care about (whether or not pushing “worked”), we need a way to parse EVM output. execCall has type MonadState VM =& SolCall -& m VMResult, so we need a way to check whether a given VMResult is true, false, or something else entirely. This turns out to be pretty trivial.
match :: VMResult -& Bool -& Bool
match (VMSuccess (B s)) b = s == encodeAbiValue (AbiBool b)
match _ _ = False
Now that we can check the results of pushing, we have everything we need to write the rest of the model. As before, we’ll write two C modeling pushing while the turnstile is locked and unlocked, respectively. Pushing while locked should succeed, and result in the turnstile becoming locked. Pushing while unlocked should fail, and leave the turnstile locked.
s_push_locked :: (Monad n, MonadTest m, MonadState VM m) =& Command n m ModelState
s_push_locked = Command (\s -& if s == TLocked then Just $ pure Push else Nothing)
-- We can only run this command when the turnstile is locked
(\Push -& cleanUp && execCall (&push&, []))
-- Pushing is just calling push()
[ Require $ \s Push -& s == TLocked
-- Before we push, the turnstile should be locked
, Update $ \_ Push _ -& TLocked
-- After we push, the turnstile should be locked
, Ensure $ \before after Push b -& do before === TLocked
-- As before
assert (match b False)
-- Pushing should fail
after === TLocked
-- As before
s_push_unlocked :: (Monad n, MonadTest m, MonadState VM m) =& Command n m ModelState
s_push_unlocked = Command (\s -& if s == TUnlocked then Just $ pure Push else Nothing)
-- We can only run this command when the turnstile is unlocked
(\Push -& cleanUp && execCall (&push&, []))
-- Pushing is just calling push()
[ Require $ \s Push -& s == TUnlocked
-- Before we push, the turnstile should be unlocked
, Update $ \_ Push _ -& TLocked
-- After we push, the turnstile should be locked
, Ensure $ \before after Push b -& do before === TUnlocked
-- As before
assert (match b True)
-- Pushing should succeed
after === TLocked
-- As before
If you can recall the image from Step 0, you can think of the states we enumerated there as the shapes and the transitions we wrote here as the arrows. Our arrows are also equipped with some rigid invariants about the conditions that must be satisfied to make each state transition (that’s our Ensure above). We now have a language that totally describes our state machine, and we can simply describe how its statements compose to get a Property!
Step 2: Write a property
This composition is actually fairly simple, we just tell Echidna to execute our actions sequentially, and since the invariants are captured in the actions themselves, that’s all that’s required to test! The only thing we need now is the actual subject of our testing, which, since we work in any MonadState VM, is just a VM, which we can parametrize the property on.
prop_turnstile :: VM -& property
prop_turnstile v = property $ do
actions &- forAll $ Gen.sequential (Range.linear 1 100) initialState
[s_coin, s_push_locked, s_push_unlocked
-- Generate between 1 and 100 actions, starting with a locked (model) turnstile
evalStateT (executeSequential initialState actions) v
-- Execute them sequentially on the given VM.
You can think of the above code as a function that takes an EVM state and returns a hedgehog-checkable assertion that it implements our (haskell) state machine definition.
Step 3: Test
With this property written, we’re ready to test some Solidity! Let’s spin up ghci to check this property with Echidna.
λ& (v,_,_) &- loadSolidity &solidity/turnstile/turnstile.sol& -- set up a VM with our contract loaded
λ& check $ prop_turnstile v -- check that the property we just defined holds
? passed 10000 tests.
It works! The Solidity we wrote implements our model of the turnstile state machine. Echidna evaluated 10,000 random call sequences without finding anything wrong.
Now, let’s find some failures. Suppose we initialize the contract with the turnstile unlocked, as below. This should be a pretty easy failure to detect, since it’s now possible to push successfully without putting a coin in first.
We can just slightly modify our initial contract as below:
contract Turnstile {
bool private locked = // initial state is unlocked
function coin() {
function push() returns (bool) {
if (locked) {
return(false);
return(true);
And now we can use the exact same ghci commands as before:
λ& (v,_,_) &- loadSolidity &solidity/turnstile/turnstile_badinit.sol&
λ& check $ prop_turnstile v
? failed after 1 test.
┏━━ examples/state-machine/StateMachine.hs ━━━
49 ┃ s_push_locked :: (Monad n, MonadTest m, MonadState VM m) =& Command n m ModelState
50 ┃ s_push_locked = Command (\s -& if s == TLocked then Just $ pure Push else Nothing)
(\Push -& cleanUp && execCall (&push&, []))
[ Require $ \s Push -& s == TLocked
, Update $ \_ Push _ -& TLocked
, Ensure $ \before after Push b -& do before === TLocked
assert (match b False)
^^^^^^^^^^^^^^^^^^^^^^
after === TLocked
┏━━ examples/state-machine/StateMachine.hs ━━━
69 ┃ prop_turnstile :: VM -& property
70 ┃ prop_turnstile v = property $ do
actions &- forAll $ Gen.sequential (Range.linear 1 100) initialState 72 ┃ [s_coin, s_push_locked, s_push_unlocked] ┃ │ Var 0 = Push 73 ┃ evalStateT (executeSequential initialState actions) v This failure can be reproduced by running: & recheck (Size 0) (Seed 7211471 (-8791673))
As we’d expect, our property isn’t satisfied. The first time we push it should fail, as the model thinks the turnstile is locked, but it actually succeeds. This is exactly the result we expected above!
We can try the same thing with some other buggy contracts as well. Consider the below Turnstile, which doesn’t lock after a successful push.
contract Turnstile {
bool private locked = // initial state is locked
function coin() {
function push() returns (bool) {
if (locked) {
return(false);
return(true);
Let’s use those same ghci commands one more time
λ& (v,_,_) &- loadSolidity &solidity/turnstile/turnstile_nolock.sol&
λ& check $ prop_turnstile v
? failed after 4 tests and 1 shrink.
┏━━ examples/state-machine/StateMachine.hs ━━━
49 ┃ s_push_locked :: (Monad n, MonadTest m, MonadState VM m) =& Command n m ModelState
50 ┃ s_push_locked = Command (\s -& if s == TLocked then Just $ pure Push else Nothing)
(\Push -& cleanUp && execCall (&push&, []))
[ Require $ \s Push -& s == TLocked
, Update $ \_ Push _ -& TLocked
, Ensure $ \before after Push b -& do before === TLocked
assert (match b False)
^^^^^^^^^^^^^^^^^^^^^^
after === TLocked
┏━━ examples/state-machine/StateMachine.hs ━━━
69 ┃ prop_turnstile :: VM -& property
70 ┃ prop_turnstile v = property $ do
[s_coin, s_push_locked, s_push_unlocked]
│ Var 0 = Coin
│ Var 1 = Push
│ Var 3 = Push
evalStateT (executeSequential initialState actions) v
This failure can be reproduced by running:
& recheck (Size 3) (Seed 084861 (-5641335))
When we insert a coin then push twice, the second should fail. Instead, it succeeds. Note that in all these failures, Echidna finds the minimal sequence of actions that demonstrates the failing behavior. This is because of Hedgehog’s shrinking features, which provide this behavior by default.
More broadly, we now have a tool that will accept arbitrary contracts (that implement the push/coin ABI), check whether they implement our specified state machine correctly, and return either a minimal falsifying counterexample if they do not. As a Solidity developer working on a turnstile contract, I can run this on every commit and get a simple explanation of any regression that occurs.
Concluding Notes
Hopefully the above presents a motivating example for testing with Echidna. We wrote a simple description of a state machine, then tested four different
each case yielded either a minimal proof the contract did not implement the machine or a statement of assurance that it did.
If you’d like to try implementing this kind of testing yourself on a , use this
we wrote for a workshop.
Welcome to the third post in our series about osquery. So far, we’ve described
they’ve encountered. For our third post, we focus on the future of osquery. We asked users, “What do you wish osquery could do?” The answers we received ranged from small requests to huge advancements that could disrupt the incident-response tool market. Let’s dive into those ‘super features’ first.
osquery super features
Some users’ suggestions could fundamentally expand osquery’s role from an incident detection tool, potentially allowing it to steal significant market share from commercial tools in doing prevention and response (we listed a few of these in our ). This would be a big deal. A free and open source tool that gives security teams access to incident response abilities normally reserved for customers of expensive paid services would be a windfall for the community. It could democratize fleet security and enhance the entire community’s defence against attackers. Here are the features that could take osquery to the next level:
Writable access to endpoints
What it is: Currently, osquery is limited to read-only access on endpoints. Such access allows the program to detect and report changes in the operating systems it monitors. Write-access via an osquery extension would allow it to edit registries in the operating system and change the way endpoints perform. It could use this access to enforce security policies throughout the fleet.
Why it would be amazing: Write-access would elevate osquery from a detection tool to the domain of prevention. Rather than simply observing system issues with osquery, write-access would afford you the ability to harden the system right from the SQL interface. Application whitelisting and enforcement, managing licenses, partitioning firewall settings, and more could all be available.
How we could build it: If not built correctly, write-access in osquery could cause more harm than good. Write-access goes beyond the scope of osquery core. Some current users are only permitted to deploy osquery throughout their fleet because of its limited read-only permissions. Granting write-access through osquery core would bring heightened security risks as well as potential for system disruption. The right way to implement this would be to make it available to extensions that request the functionality during initialization and minimize the impact this feature has on the core.
IRL Proof: In fact, we have a
waiting on approval that would support write-access through extensions! The code enables write-permissions for extensions but also blocks write-permissions for tables built into core.
We built this feature in support of a client who wanted to block malicious IP addresses, domains and ports for both preventative and reactive use-cases. Once this code is committed, our clients will be able to download our osquery firewall extension to use osquery to partition firewall settings throughout their fleets.
Event-triggered responses
What it is: If osquery reads a log entry that indicates an attack, it could automatically respond with an action such as quarantining the affected endpoint(s). This super feature would add automated prevention and incident response to osquery’s capabilities.
Why it would be amazing: This would elevate osquery’s capabilities to those of commercial vulnerability detection/response tools, but it would be transparent and customizable. Defense teams could evaluate, customize, and match osquery’s incident-response capabilities to their companies’ needs, as a stand-alone solution or as a complement to another more generic response suite.
How we could build it: Automated event response for osquery could be built flexibly to allow security teams to define their own indicators of incidents and their preferred reactions. Users could select from known updated databases: URL reputation via VirusTotal, file reputation via ReversingLabs, IP reputation of the remote addresses of active connections via OpenDNS, etc. The user could pick the type of matching criteria (e.g., exact, partial, particular patterns, etc.), and prescribe a response such as ramping up logging frequency, adding an associated malicious ID to a firewall block list, or calling an external program to take an action. As an additional option, event triggering that sends logs to an external analysis tool could provide more sophisticated response without damaging endpoint performance.
IRL Proof: Not only did multiple interviewees l some teams have started to build rudimentary versions of it. As discussed in “”, we spoke with one team who built incident alerting with osquery by piping log data into ElasticSearch and auto-generated Jira tickets through
upon anomaly detection. This example doesn’t demonstrate full response capability, but it illustrates how useful just-in-time business process reaction to incidents is possible with osquery. If osquery can monitor event-driven logs (FIM, process auditing, etc), trigger an action based on detection of a certain pattern, and administer a protective response, it can provide an effective endpoint protection platform.
Technical debt overhaul
What it is: Many open source projects carry ‘technical debt.’ That is, some of the code engineering is built to be effective for short-term goals but isn’t suitable for long-term program architecture. A distributed developer community each enhancing the technology for slightly different requirement exacerbates this problem. Solving this problem requires costly coordination and effort from multiple community members to rebuild and standardize the system.
Why it would be amazing: Decreasing osquery’s technical debt would upgrade the program to a standard that’s adoptable to a significantly wider range of security teams. Users in our
research cited performance effects and reliability among organizational leadership’s top concerns for adopting osquery. Ultimately, the teams we interviewed won the argument, but there are likely many teams who didn’t get the green light on using osquery.
How we could build it: Tackling technical debt is hard enough within an organization. It’s liable to be even harder in a distributed community. Unless developers have a specific motivation for tackling very difficult high-value inefficiencies, the natural reward for closing an issue biases developers toward smaller efforts. To combat this, leaders in the community could dump and sort all technical debt issues along a matrix of value and time, leave all high-value/low-time issues for individual open source developers, and pool community resources to resolve harder problems as full-fledged development projects.
IRL Proof: We know that pooling community resources to tackle technical debt works. We’ve been doing it for over a year. Trail of Bits has been commissioned by multiple companies to build features and fixes too big for the open source community. We’ve leveraged this model to , , and much more that we’re excited to share with the public over the coming months. Often, multiple clients are interested in building the same things. We’re able to pool resources to make the project less expensive for everyone involved while the entire community benefits.
Other features users want
osquery shows considerable potential to grow beyond endpoint monitoring. However, the enterprise security teams and developers whom we interviewed say that the open source tool has room for improvement. Here are some of the other requests we heard from users:
Guardrails & rules for queries: Right now, a malformed query or practice can hamper the user’s workflow. Interviewees wanted guidance on targeting the correct data, querying at correct intervals, gathering from recommended tables, and customized recommendations for different environments.
Enhance Deployment Options: Users sought better tools for deploying throughout fleets and keeping these implementations updated. Beyond recommended QueryPacks, administrators wanted to be able to define and select platform-specific configurations of osquery across multi-platform endpoints. Automatically detecting and deploying configurations for unique systems and software was another desired feature.
Integrated Testing, Debugging, and Diagnostics: In addition to the , users wanted more resources for testing and diagnosing issues. New tools should help improve reliability and predictability, avoid performance issues, and make osquery easier to use.
Enhanced Event-Driven Data Collection: osquery has support for event-based data collection through , , and other tables. However, these data sources suffer from logging implementation issues and are not supported on all platforms. Better event-handling configurations, published best practices, and guardrails for gathering data would be a great help.
Enhanced Performance Features: Users want osquery to do more with fewer resources. This would either lead to overall performance enhancements, or allow osquery to operate on endpoints with low resource profiles or mission-critical performance requirements.
Better Configuration Management: Enhancements such as custom tables and osqueryd scheduled queries for differing endpoint environments would make osquery easier to deploy and maintain on a growing fleet.
Support for Offline Endpoint Logging: Users reported a desire for forensic data availability to support remote endpoints. This would require offline endpoints to store data locally –- including storage of failed queries –- and push to the server upon reconnection
Support for Common Platforms: Facebook built osquery for its fleet of macOS- and Linux-based endpoints. PC sysadmins were out of luck until our Windows
last year. Support for other operating systems has been growing steadily thanks to the development community’s efforts. Nevertheless, there are still limitations. Think of this as one umbrella feature request: support for all features on all operating systems.
The list keeps growing
Unfortunately for current and prospective osquery users, Facebook can’t satisfy all of these requests. They’ve shared a tremendous gift by open sourcing osquery. Now it’s up to the community to move the platform forward.
Good news: none of these feature requests are unfeasible. The custom engineering is just uneconomical for individual organizations to invest in.
In the final post in this series, we’ll propose a strategy for osquery users to share the cost of development. Companies that would benefit could pool resources and collectively target specific features.
This would accelerate the rate at which companies could deprecate other full-suite tools that are more expensive, less flexible and less transparent.
If any of these items resonate with your team’s needs, or if you use osquery currently and have another request to add to the list, please .
You’ve just approved an audit of your codebase. Do you:
Send a copy of the repository and wait for the auditors’ reports, or
Take the extra effort to set the auditors up for success?
By the end of the audit, the difference between these answers will lead to profoundly disparate results. In the former case, you’ll waste money, lose time, and miss security issues. In the latter case, you’ll reduce your risk, protect your time, and get more valuable security guidance.
It’s an easy choice, right?
Glad you agree.
Now, here’s how to make that audit more effective, valuable, and satisfying for everybody involved.
Set a goal for the audit
This is the most important step of an audit, and paradoxically the one most often overlooked. You should have an idea of what kind of question you want answered, such as:
What’s the overall level of security for this product?
Are all client data transactions handled securely?
Can a user leak information about another user?
Knowing your biggest area of concern will help the auditing team tailor their approach to meet your needs.
Resolve the easy issues
Handing the code off to the auditing team is a lot like releasing the product: the
the code, the better everything will go. To that end:
Enable and address compiler warnings. Go after the easy stuff first: turn on every single compiler warning you can find, understand each warning, then fix your code until they’re all gone. Upgrade your compiler to the latest version, then fix all the new warnings and errors. Even innocuous seeming warnings can indicate problems lying in wait.
Increase unit and feature test coverage. Ideally this has been part of the development process, but everyone slips up, tests don’t get updated, or new features don’t quite match the old integrations tests. Now is the time to update the tests and run them all.
Remove dead code, stale branches, unused libraries, and other extraneous weight. You may know which branch is active and which is dead but the auditors won’t and will waste time investigating it for potential issues. The same goes for that new feature that hasn’t seen progress in months, or that third-party library that doesn’t get used anymore.
Some issues will persist — a patch that isn’t quite ready, or a refactor that’s not integrated yet. Document any incomplete changes as thoroughly as possible, so that your auditors don’t waste a week digging into code that will be gone in two months’ time.
Document, Document, Document
Think of an audit team as a newly hired, fu skilled at what they do, but unfamiliar with your product and code base. The more documentation, the faster they’ll get up to speed and the sooner they’ll be able to start their analysis.
Describe what your product does, who uses it, and how. The most important documentation is high level: what does your product do? What do users want from it? How does it achieve that goal? Use clear language to describe how systems interact and the rationale for design decisions made during development.
Add comments in-line with the code. Functions should have comments containing high-level descriptions of their intended behavior. Complicated sections of code should have comments describing what is happening and why this particular approach was chosen.
Label and describe your tests. More complicated tests should describe the exact behavior they’re testing. The expected results of tests, both positive and negative, should be documented.
Include past reviews and bugs. Previous audit reports can provide guidance to the new audit team. Similarly, documentation regarding past security-relevant bugs can give an audit team clues about where to look most carefully.
Deliver the code batteries included
Just like a new fully remote developer, the audit team will need a copy of the code and clear guidance on how to build and deploy your application.
Prepare the build environment. Document the steps to create a build environment from scratch on a computer that is fully disconnected from your internal network. Where relevant, be specific about software versions. Walk through this process on your own to ensure that it is complete. If you have external dependencies that are not publicly available, include them with your code. Fully provisioned virtual machine images are a great way to deliver a working build environment.
Document the build process. Include both the debug and release build processes, and also include steps on how to build and run the tests. If the test environment is distinct from the build environment, include steps on how to create the test environment. A well-documented build process enables an auditor to run static analysis tools far more efficiently and effectively.
Document the deploy process. This includes how to build the deployment environment. It is very important to list all the specific versions of external tools and libraries for this process, as the deployment environment is a considerable factor in evaluating the security of your product. A well-documented deployment process enables an auditor to run dynamic analysis tools in a real world environment.
The payoff
At this point you’ve handed off your code, documentation, and build environment to the auditors. All that prep work will pay off. Rather than puzzling over how to build your code or what it does, the audit team can immediately start work integrating advanced analysis tools, writing custom fuzzers, or bringing custom internal tools to bear. Knowing your specific goals will help them focus where you want them to.
An audit can produce a lot of insight into the security of your product. Having a clear goal for the audit, a clean codebase, and complete documentation will not only help the audit, it’ll make you more confident about the quality of the results.
Interested in getting an audit?
to find out what we can do for you.
Resolve the easy issues
Enable and address every last compiler warning.
Increase unit and feature test coverage.
Remove dead code, stale branches, unused libraries, and other extraneous weight.
Describe what your product does, who uses it, why, and how it delivers.
Add comments about intended behavior in-line with the code.
Label and describe your tests and results, both positive and negative.
Include past reviews and bugs.
Deliver the code batteries included
Document the steps to create a build environment from scratch on a computer that is fully disconnected from your internal network. Include external dependencies.
Document the build process, including debugging and the test environment.
Document the deploy process and environment, including all the specific versions of external tools and libraries for this process.
This is Part 3 in a series of posts about the Binary Ninja Intermediate Language (BNIL) family. You can read Part 1
and Part 2 .
In my previous post, I demonstrated how to leverage the Low Level IL (LLIL) to write an architecture-agnostic plugin that could devirtualize C++ virtual functions. A lot of new and exciting features have been added to Binary N in particular, Medium Level IL (MLIL) and Single Static Assignment (SSA) form. In this post, I’m going to discuss both of these and demonstrate one fun use of them: automated vulnerability discovery.
Plenty of static analyzers can perform vulnerability discovery on source code, but what if you only have the binary? How can we model a vulnerability and then check a binary to see if it is vulnerable? The short answer: use Binary Ninja’s MLIL and SSA form. Together, they make it easy to build and solve a system of equations with a theorem prover that takes binaries and turns them, alchemy-like, into vulnerabilities!
Let’s walk through the process with everyone’s favorite hyped vulnerability of yesteryear, Heartbleed.
Hacking like it’s 2014: Let’s find Heartbleed!
For those who might not remember or be familiar with the Heartbleed vulnerability, let’s run through a quick refresher.
was a remote information-disclosure vulnerability in OpenSSL 1.0.1 &#.1f that allowed an attacker to send a crafted TLS heartbeat message to any service using TLS. The message would trick the service into responding with up to 64KB of uninitialized data, which could contain sensitive information such as private cryptographic keys or personal data. This was possible because OpenSSL used a field in the attacker’s message as a size parameter for malloc and memcpy calls without first validating that the given size was less than or equal to the size of the data to read. Here’s a snippet of the vulnerable code in OpenSSL 1.0.1f, from tls1_process_heartbeat:
/* Read type and payload length first */
hbtype = *p++;
n2s(p, payload);
/* Skip some stuff... */
if (hbtype == TLS1_HB_REQUEST)
unsigned char *buffer, *
/* Allocate memory for the response, size is 1 bytes
* message type, plus 2 bytes payload length, plus
* payload, plus padding
buffer = OPENSSL_malloc(1 + 2 + payload + padding);
/* Enter response type, length and copy payload */
*bp++ = TLS1_HB_RESPONSE;
s2n(payload, bp);
memcpy(bp, pl, payload);
/* Random padding */
RAND_pseudo_bytes(bp, padding);
r = ssl3_write_bytes(s, TLS1_RT_HEARTBEAT, buffer, 3 + payload + padding);
Looking at the code, we can see that the size parameter (payload) comes directly from the user-controlled TLS heartbeat message, is converted from network-byte order to host-byte order (n2s), and then passed to OPENSSL_malloc and memcpy with no validation. In this scenario, when a value for payload is greater than the data at pl, memcpy will overflow from the buffer starting at pl and begin reading the data that follows immediately after it, revealing data that it shouldn’t. The fix in 1.0.1g was pretty simple:
hbtype = *p++;
n2s(p, payload);
if (1 + 2 + payload + 16 & s-&s3-&rrec.length)
return 0; /* silently discard per RFC 6520 sec. 4 */
This new check ensures that the memcpy won’t overflow into different data.
Back in 2014, Andrew blogged about . A clang analyzer plugin runs on source code, how could we find the same vulnerability in a binary if we didn’t have the source for it? One way: build a model of a vulnerability by representing MLIL variables as a set of constraints and solving them with a theorem prover!
Model binary code as equations with z3
A theorem prover lets us construct a system of equations and:
Verify whether those equations contradict each other.
Find values that make the equations work.
For example, if we have the following equations:
2x + 3 = 7
A theorem prover could tell us that a) a solution does exist for these equations, meaning that they don’t contradict each other, and b) a solution to these equations is x = 2 and y = 6.
For the purposes of this exercise, I’ll be using the
from Microsoft Research. Using the z3 Python library, the above example would look like the following:
&&& from z3 import *
&&& x = Int('x')
&&& y = Int('y')
&&& s = Solver()
&&& s.add(x + y == 8)
&&& s.add(2*x + 3 == 7)
&&& s.check()
&&& s.model()
[x = 2, y = 6]
Z3 tells us that the equations can be satisfied and provides values to solve them. We can apply this technique to modeling a vulnerability. It turns out that assembly instructions can be modeled as algebraic statements. Take the following snippet of assembly:
lea eax, [ebx+8]
cmp eax, 0x20
jle allocate
call malloc
When we lift this assembly to Binary Ninja’s LLIL, we get the following graph:
Figure 1. LLIL makes it easy to identify the signed comparison conditional.
In this code, eax takes the value of ebx and then adds 8 to it. If this value is above 0x20, an interrupt is raised. However, if the value is less than or equal to 0x20, the value is passed to malloc. We can use LLIL’s output to model this as a set of equations that should be unsatisfiable if an integer overflow is not possible (e.g. there should never be a value of ebx such that ebx is larger than 0x20 but eax is less than or equal to 0x20), which would look something like this:
eax = ebx + 8
ebx & 0x20
eax &= 0x20
What happens if we plug these equations into Z3? Not exactly what we’d hope for.
&&& eax = Int('eax')
&&& ebx = Int('ebx')
&&& s = Solver()
&&& s.add(eax == ebx + 8)
&&& s.add(ebx & 0x20)
&&& s.add(eax &= 0x20)
&&& s.check()
There should be an integer overflow, but our equations were unsat. This is because the Int type (or “sort” in z3 parlance) represents a numb}