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BlackHat and Defcon 2023
by Dave Aitel 16 Aug '23

16 Aug '23

The Vegas security conferences used to feel like diving into a river. While yes, you networked and made deals and talked about exploits, you also felt for currents and tried to get a prediction of what the future held. A lot of this was what the talks were about. But you went to booths to see what was selling, or what people thought was selling, at least. But it doesn't matter anymore what the talks are about. The talks are about everything. There's a million of them and they cover every possible topic under the sun. And the big corpo booths are all the same. People want to sell you XDR, and what that means for them is a per-seat or per-IP charge. When there's no differentiation in billing, there's no differentiation in product. That doesn't mean there aren't a million smaller start-ups with tiny cubicles in the booth-space, like pebbles on a beach. Hunting through them is like searching for shells - for every Thinkst Canary there's a hundred newly AI-enabled compliance engines. DefCon and Blackhat in some ways used to be more international as well - but a lot of the more interesting speakers can't get visas anymore or aren't allowed to talk publicly by their home countries. If you've been in this business for a while, you have a dreadful fear of being in your own bubble. To not swim forward is to suffocate. This is what drove you to sit in the front row of as many talks as possible at these two huge conferences, hung over, dehydrated, confused by foreign terminology in a difficult accent. But now you can't dive in to make forward progress. Vegas is even more of a forbidding dystopia, overloaded with crowds so heavy it can no longer feed them or even provide a contiguous space for the ameba-like host to gather. Talks echo and muddle in cavernous rooms with the general acoustics of a high school gymnasium. You are left with snapshots and fragmented memories instead of a whole picture. For me, one such moment was a Senate Staffer, full of enthusiasm, crowing about how smart the other people working on policy and walking the halls of Congress were - experts and geniuses at healthcare, for example! But if our cyber security policy matches our success at a health system we are doomed. I brought my kids this year and it helps to be able to see through the chaos with new eyes. What's "cool" I asked? in the most boomery way possible. Because I know Jailbreaking an AI to say bad things is not it, even though it had all the political spotlights in the world focused on examining the "issue". The more crowded the field gets, the less immersion you have. Instead of diving in you are holding your palm against the surface of the water, hoping to sense the primordial tube worms at the sea vents feeding on raw data leagues below you. "Take me to the beginning, again" you say to them, through whatever connection you can muster. -dave

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More Neo4j
by Dave Aitel 03 Aug '23

03 Aug '23

https://www.youtube.com/live/YY-ugAHPu4M?feature=share&t=1057 I have on my todo list to reply to our thread last month, but in the meantime, here is a video that goes over all the lessons learned from my last couple years doing Neo4j. But as a reminder, we should still port Ghidra to Neo4j. :) -dave

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Tooling, Graph Databases, etc.
by Dave Aitel 27 Jun '23

27 Jun '23

There's a new Ghidra release last week! Lots of improvements to the debugger, which is awesome. But this brings up some thoughts that have been triggering my vulnerability-and-exploitation-specific OCD for some time now. Behind every good RE tool is a crappy crappy database. Implicitly we, as a community, understand there is no good reason that every reverse engineering project needs to implement a key-value store, or a B-Tree <https://github.com/NationalSecurityAgency/ghidra/tree/master/Ghidra/Framewo…>, or partner with a colony of bees which maintain tool state by various wiggly dances. But yet each and every tool has a developer with decades of reverse engineering experience on rare embedded platforms either building custom indexes in a pale imitation of a real DB structure or engaging in insect-based diplomacy efforts. I think the Ghidra team (and Binja/IDA teams!) are geniuses, but they are probably NOT geniuses at building database engines. And reading through the issues <https://github.com/NationalSecurityAgency/ghidra/issues/985> with ANY reverse engineering product you find that performance even for the base feature-set is a difficult ask. My plea is this: We need to port Ghidra to Neo4j as soon as possible. Having a real Graph DB store underneath Ghidra solves the scalability issues. I understand the difficulty here is: There are few engineers who understand both Neo4j and reverse engineering to the point where this can be done. I mean, why do it in Neo4j and not PostGres? An argument can be made for both, in the sense that PostGres is truly Free and the most solid DB on the market. The pluses for Neo4j are that RE data is typically graph-based more than linear. I spent the last two years learning graph dbs, out of some masochistic desire and ended up getting certified - and I can still RE a little bit. I will manage the team porting Ghidra to Neo4j if someone funds it. :) Either way, sooner is better than later. There are so many companies and people relying on these tools that it seems silly to do anything else. -dave P.S. Yes, I remember BinNavi used MsSQL installs for its data, and this was annoying to install but ... I get why Halvar did it at the time. It's because he had real work to do and building a DB was not it. I can only assume Reven doesn't use their own DB? I mean the benefits for interoperability would be huge between tools. . . like literally everything you want to do with these tools is better with a real DB underneath.

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A graph disassembler
by Dave Aitel 08 Jun '23

08 Jun '23

Lately I've been watching a lot of online security talks - the new thing for conferences to do is publish them almost immediately, which is amazing. So like, today I watched Chompie's talk: https://www.sstic.org/2023/presentation/deep_attack_surfaces_shallow_bugs/ (I was honestly hoping it went from RCE to logic bug and allowed you to log in, but maybe left as an exercise for the reader). And yesterday I watched Natalie's talk: https://www.youtube.com/watch?v=quw8SnmMWg4&t=663s&ab_channel=OffensiveCon (I'm still a bit confused as to how you connect to a phone's baseband with SIP, but maybe I will ask later at some point). Does the baseband just have some TCP ports open for RTC shenanigans? If so, that's great, #blessed, etc. I actually forgot to post my own talk here, so if you want to watch that, it's here: https://www.youtube.com/watch?v=BarJCn4yChA&t=1669s&ab_channel=OffensiveCon My talk is not actually a call to hack enterprise products - which ya'll are clearly already doing a lot of (I'm just assuming there are members of the FIN11 ransomware crew on this list somewhere). It's more about understanding which business models lead to easy bugs - enterprise software obviously being one of them, but, for example, DRM components are another one. There is an endless supply really. Today I noticed Barracuda is saying that if your appliance gets hacked <https://www.bleepingcomputer.com/news/security/barracuda-says-hacked-esg-ap…>, you should replace it immediately. It is now trash, or "e-waste" if you prefer. This is a surprisingly honest thing to say. Previously appliance companies who get hacked say things like "Meh? Upgrade pls! Don't forget to change your passwords!" because as we all know, the firmware <https://arstechnica.com/information-technology/2023/03/malware-infecting-wi…> and boot partitions inside expensive security appliances are all protected by angry leprechauns, which is why it's still ok in 2023 to have Perl installed on them, even if you don't know what a ../.../ does in a tar file. This honesty would be nice if it also applied to our government agencies - like instead of this very long report CISA <https://www.cisa.gov/news-events/cybersecurity-advisories/aa21-110a#:~:text….> put out about what to do if you think your Pulse Secure VPN was hacked, which recommends performing a factory reset, updating your appliance to the very latest version, and then calling your therapist to have a good cry about it, they should have instead said: "Yes, your appliance did at one point control authentication for everyone accessing your network, but because it had issues with gzip files and opening URIs, it is now e-waste." Crap, I forgot to write about the graph disassembler I want and why. Tomorrow, for sure. -dave

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Yawps from the rooftops
by Dave Aitel 05 Jun '23

05 Jun '23

[image: image.png]https://twitter.com/thezdi/status/1638617627626176513 [image: image.png] Yawps So one thing I have as a "lessons learned" from the past 20 years is that security is not a proactive sport. In fact, we are all experts at running to where the ball _was_as opposed to where it is _going_. Like, if you listen to Risky Biz this week, Patrick asks Metlstorm whether it's time to go out and replace all the old enterprise file sharing systems <https://twitter.com/vxunderground/status/1641629743534559233?s=20> you have around, proactively. And the answer, from Metl, who's hacked into every org in Oceania for the past 20 years, is "yeah, this is generating huge return on investment for the ransomware crews so they're just going to keep doing it, and being proactive might be a great idea." But what he didn't say, but clearly had in his head was "but lol, nobody is going to actually do that. So good luck out there chooms!" At some level, STIX and TAXII and the whole CTI market are about passing around information on what someone _might_ have used to hack something, at some point in the _distant past_. It's a paleontology of hackers past - XML schemas about huge ancient reptiles swimming in the tropical seas of your networks, the taxonomies of extinct orders we now know only through a delicate finger-like flipper bone or a clever piece of shellcode. -dave

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Fussing about with fuzzers
by Dave Aitel 22 May '23

22 May '23

So last week at offensivecon I watched a talk on Fuzzilli ( https://github.com/googleprojectzero/fuzzilli) which, I have to admit I had no idea what it was. Obviously I knew it was a Googlely Javascript fuzzer, finding bugs. But I did not realize that it was applying mutations to its own intermediate language which it then compiled to Javascript. I just assumed it was, like most fuzzers, mutating the javascript directly (f.e. https://sean.heelan.io/2016/04/26/fuzzing-language-interpreters-using-regre… ). But having an IL designed for fuzzing-related mutations is clearly a great idea! And this year, they've expanded on that to build a Javascript->Fuzzilli compiler/translation layer. So you can pass in sample Javascript and then it will create the IL and then it will mutate the IL. The reason this is necessary is that Javascript is. like almost all modern languages, extremely complicated underneath the covers, so in order to generate crashes you may need to have a lot of different fields set properly in a particular order in a structure. They try to do some introspection on objects and generate their samples from that as well, but there's no beating "real user code" for learning how an object needs to be created and used. These advances generate a lot more bugs! In theory none of these bugs matter in the future because of the mitigations (no pointers outside the Javascript gigacage!) going into place by the very authors of the fuzzer? (I have my doubts, but we all will live and learn?) It would be...very cool, I think, if Bard or another LLM was the one doing the Javascript sample generation as well. If you think about it, these LLMs all have a good understanding of Javascript and you can give them various weird tasks to do, and let them generate your samples, and then when a crash happens you can have them mutate around that crash, or if you have a sample not getting any more code coverage you can have them mutate that sample to attempt to make it weirder. :) -dave

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Knowledge Graph + AI = ?
by Dave Aitel 09 May '23

09 May '23

*Logical Operations on Knowledge Graphs:* So if you've spent enough time looking at graph databases, you will invariably run into people who are obsessed with "ontologies". The basic theory being that if you've already organized your data in some sort of directed graph, maybe you can then apply a logical ruleset to those relationships and infer knowledge about things you didn't already know, which could be useful? There are a lot of people trying to do this with SBOMs and I...wish them the best. In real life I think it's basically impossible to create a large, useful, graph database+inference engine that has data clean enough for anything useful. Also the word *ontology* is itself very annoying. But philosophically, while any complex enough data set will have to embrace paradoxes, you can get a lot of value out of putting some higher level structure based on the text in your data. And this is where modern AI comes in - in specific, the tree of "Natural Language Understanding" that broke off from Chomsky-esque-and-wrong "Natural Language Processing" some time ago. One article covering this topic is here <https://medium.com/@anthony.mensier/gpt-4-for-defense-specific-named-entity…>, which combines entity extraction and classification in order to look into finding military topics in an article. But these techniques can be abstracted and broadened as a general purpose and very useful algorithm: Essentially you want to extract keywords from text fields within your graph data, then relate those keywords to each other, which gives you conceptual groupings and allows you to make further queries that uncover insights about those groups. *Our Solution:* One of the team-members over at Margin Research working on SocialCyber <https://www.darpa.mil/program/hybrid-ai-to-protect-integrity-of-open-source…> with me, Matt Filbert, came up with the idea of using OpenAI's GPT to get hashtags from text, which it does very very well. If you store these as nodes you get something like the picture below (note that hashtags are BASED on the text, but they are NOT keywords and may not be in the text itself): [image: image.png] Next you want to figure out how topics are related to each other! Which you can do in a thousand different ways - the code words to search on are "Node Similarity" - but almost all those ways will either not work or create bad results because you have a very limited directional graph of just "Things->Topics". In the end we used a modified Jaccardian algo (aka, you are similar if you have shared parents), which I call Daccardian because it creates weighted directed graphs (which comes in handy later): [image: image.png] So once you've done that, you get this kind of directed graph: [image: image.png] From here you could build communities of related topics using any community detection algorithm, but even just being able to query against them is extremely useful. In theory you could query just against one topic at a time, but because of the way your data is probably structured, you want both that topic, and any closely related topics to be included. So for example, looking for Repos that have topics that either are "#UI" or closely related, can be queried like this (not all topics are shown because of the LIMIT clause): [image: image.png] *Some notes on AI Models:* OpenAI's APIs are a bit slow, and often throw errors randomly, which is fun to handle. And of course, when doing massive amounts of inference, it's probably cheaper to run your own equipment, which will leave you casting about on Huggingface like a glow worm in a dark cave for a model that can do this and is open source. I've tried basically all of them and they've all started out promising but then been a lot worse than ChatGPT 3.5. You do want one that is multilingual, and Bard might be an option when they open their API access up. There's a significant difference between the results from the big models and the little ones, in contrast to the paper that just "leaked" from Google <https://www.semianalysis.com/p/google-we-have-no-moat-and-neither> about how small tuned models are going to be just as good as bigger models (which they are not!). One minor exception is the new Mosaic model ( https://huggingface.co/spaces/mosaicml/mpt-7b-instruct) which is multilingual and four times cheaper than OpenAI but it's also about 1/4th as good. It may be the first "semi-workable" open model though, which is a promising sign and it may be worth moving to this if you have data you can't run through an open API for some reason. *Conclusion:* If you have a big pile of structured data, you almost certainly have natural language data that you want to capture as PART of that structure, but this would have been literally impossible six months ago before LLMs. Using this AI-tagging technique and doing some basic graph algorithms can really open up the power of your queries to take the most valuable part of your information into account, while not losing the performance and scalability of having it in a database in the first place. Thanks for reading, Dave Aitel PS: I have a dream, and that dream is to convert Ghidra into a Graph Database as a native format so we can use some of these techniques (and code embeddings) as a native feature. If you sit next to the Ghirda team, and you read this whole post, give them a poke for me. :)

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Performance thoughts
by Dave Aitel 28 Apr '23

28 Apr '23

So my first thought is that performance measurement tools seem exactly aimed at a lot of security problems but performance people are extremely reluctant <https://aus.social/@brendangregg/110276319669838295> to admit that because of the drama involved in the security market. Which is very smart of them! :) Secondly, I wanted to re-link to Halvar's QCon keynote <https://docs.google.com/presentation/d/1wOT5kOWkQybVTHzB7uLXpU39ctYzXpOs2xV…>. He has a section on the difficulties of getting good performance benchmarks, which typically you would do as part of your build chain. So in theory, you have a lot of compilation features you can twiddle when compiling and you want to change those values, compile your program, and get a number for how fast it is. But this turns out to basically be impossible in the real world for reasons I'll let him explain in his presentation (see below). [image: image.png] A lot of these problems with performance seem only solvable by a continuous process of evolutionary algorithms - where you have a population of different compilation variables, and you probably introduce new ones over time, and you kill off the cloud VMs where you're getting terrible performance under real-world situations and let the ones getting good or average performance thrive. I'm sure this is being done, and probably if I listened to more of Dino dai Zovi's talks I'd know where and how, but aside from having performance implications, it also has security implications because it will tend towards offering offensive implants value for becoming less parasitic and more symbiotic. -dave

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LSU is hiring CS Professors with RE and binary exploitation experience
by Andrew Case 30 Mar '23

30 Mar '23

The Computer Science department at Louisiana State University (LSU) is currently hiring for many faculty positions related to applied cyber security. Courses taught inside this department include reverse engineering, malware analysis, binary exploitation, memory forensics and other intensive courses related to incident response and offensive security. Ideal candidates will have significant experience with deeply technical areas of cybersecurity. LSU was recently granted the CAE-CO designation and is one of only 21 schools nation-wide to hold it as it is the most technical designation granted by NSA and DHS. The department also runs a large SFS program for cyber security students. If you are interested in one of these positions, then please see the following link. I also ask my industry contacts to please spread the word within academic communities that you have access to: https://lsu.wd1.myworkdayjobs.com/en-US/LSU/job/3325-Patrick-F-Taylor-Hall/… The cybersecurity effort at LSU has strong support from the highest levels of the school and is rapidly expanding – so now is the perfect time to join. PS: I am not employed by LSU, but do work very closely with the CS department to ensure the courses are relevant to industry and rigorous enough for students to leave with real-world, hands-on experience. If you have questions related to the position, then please direct them to Dr. Golden Richard at LSU: https://www.cct.lsu.edu/~golden/ Thanks, Andrew

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t2'23: Call For Papers 2023 (Helsinki, Finland)
by Tomi Tuominen 12 Feb '23

12 Feb '23

Call For Papers 2023 Tired of your bosses suspecting conference trips to exotic locations being just a ploy to partake in Security Vacation Club? Prove them wrong by coming to Helsinki, Finland on May 4-5 2023! Guaranteed lack of sunburn, good potential for rain or slush. In case of great spring weather, though, no money back. CFP and registration both open. Read further if still unsure. Maui, Miami, Las Vegas, Tel Aviv or Wellington feel so much sunnier once you’ve experienced the lack of infinity pools in Northern Europe. Instead of pools and palms trees, we can offer you actual saunas and a high tech environment, which is a weird combination of demoscene, widespread Linux adoption, mobile Internet with uncapped flat rate data and a long history of IRC and imageboards. What defines a conference? For t2 it has always been that intimate welcoming atmosphere of a small event, which makes both audience and speakers approachable. There are enough regulars to create the feeling of a community, but not too many that a first-comer would feel being left out. On the content side, we have always been and always will be a technical security conference, emphasizing the cutting edge, world class research. This is an event for the community. Our focus[1] is on technical excellence, not politics or player hating. t2’23 offers you an audience with a taste for technical security presentations containing original content. This is your chance to showcase the latest research and lessons in EDR simulation and healthcheck spoofing, hardware insecurity, inferring information from interference, cloud-scale forensics or persistance automation, new vulnerability classes, AI exploitation, virtual machines inside parsers, elegant exploitation of old vulnerability classes, modern defense, dropping zero days during presentations, state of the art memory corruption mitigation bypasses, evasions, safe cracking, satellite and space security, remote vehicle access, or whatever research lights up the eyes of seasoned conference visitors. For the hackers by the hackers. The advisory board will be reviewing submissions until 2023-03-17. Slide deck submission final deadline 2023-04-20 for accepted talks. First come, first served. Submissions will not be returned. Quick facts for speakers + presentation length 60-120 minutes, in English + complimentary travel and accommodation for one person[6] + decent speaker hospitality benefits + no marketing or product propaganda Still not sure if this is for you? Check out the blast from the past[2]. The total amount of attendees, including speakers and organizers is limited to 99. Advisory Board recognize[3] the OG Finnish sauna culture is an acquired taste and can promise the lack of sweaty, partially or fully nude sauna-goers at all conference functions. [0] hunter2 [1] https://t2.fi/about/eula/ [2] https://t2.fi/schedules/ [3] https://youtu.be/Oj8JBBAM5jY?t=40 [6] except literally @nudehaberdasher and @0xcharlie How to submit Fill out the form at https://if.t2.fi/action/cfp How to register Buy your ticket at https://t2.fi/registration/

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