Co-founder & CTO at NOFire AI · Prev Distinguished Engineer / SRE at Elastic

Athens, Greece
Joined July 2014
At @NOFireAI we 'design for breach'. The AI agent in production is untrusted by default. nofire.ai/blog/design-for-br…
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Panagiotis Moustafellos retweeted
I built 𝚌𝚙𝚞-𝚌𝚑𝚊𝚝, a reproduction of @openai's findings of covert communication using the CPU. It runs on a generic host with 2+ Firecracker microVMs with no internet access. Works on x86 and even my M5 chip. I was able to chat via 3 separate mechanisms: ① CPU contention ② Cache eviction timing ③ DRAM bandwidth contention … across multiple CPUs, defeating all Firecracker's production recommendations (no SMT, no KSM, tenants pinned to different cores.) Essentially, if shared hardware is involved, there's a good chance your agents can communicate covertly. And with really decent latency. The good news: this is decidedly different from a *side-channel attack* where the agents could steal information (Meltdown/Spectre), a category of attack that providers like Vercel Sandbox mitigate. Further, in our real-world environment, these 'whispering' techniques are much harder to pull off and easier for us to monitor and detect (sampling hardware counters + lots of at-scale statistical data.) Noteworthy: ironically, OpenAI and Anthropic's models refused to do this work. Open weight models got the job done. I'm worried the labs' stance might backfire and get in the way of helping developers build correct and secure systems. e.g: building a secure sandbox requires having this kind of analysis, and without it, we'll have a less secure world.
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Panagiotis Moustafellos retweeted
Everyone who owns hardware with abominable software (like Sonos players) owes a debt of gratitude to Venkatraman Srinivasan and the rest of the eMudhra gang in Bengaluru, Karnataka. Without their gross negligence, it'd be a lot harder to counterfeit certificates and fix the sw🙏
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Panagiotis Moustafellos retweeted
We are back in London next week for Observability & SRE in Enterprise? Join and @spirosoik and @pmoust for a private roundtable about L1/L2/L3 support, coding agents and production reliability. October 22 · London
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Panagiotis Moustafellos retweeted
brig v0.4.0 gives new sandboxes their own networks by default on Linux and on macOS. Run coding agents for different projects on one machine, while keeping their dev servers and test APIs separate. In this demo, one sandbox tries to reach a web server in the other. The connection times out. We then start both with --network shared, and the same request works. You can run unrelated tasks side by side and enable network sharing when agents need to work together. #OpenSource #Sandboxing
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Panagiotis Moustafellos retweeted
Replying to @typesafeai
@typesafeai achieved 46% higher GPU throughput while training Jev using @zymtrace’s cluster-wide, continuous profiling and agentic optimization platform. See how they did it in the link below 👇
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Panagiotis Moustafellos retweeted
brig v0.4.0 limits where your coding agent can send your code and credentials. This release brings egress policy enforcement on Linux! If brig cannot enforce the policy, then the run is refused. Allow the services you need for the job. Then brig enforces your network policy outside the sandbox, so the rules also apply to the scripts and dependencies the agent runs. In this demo, an example domain works. Requests to Github API and a direct connection to 1.1.1.1 are blocked, even from a root shell inside the sandbox. #OpenSource #Sandboxing
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Panagiotis Moustafellos retweeted
Just accept it, AI writes better code than you on average. It's fine.
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Opus 5.5 just deleted my entire fucking C drive. Thank GOD I have daily backups running to my Synology NAS, but holy fucking shit. This is insane. If I didn't have these backups running I'd be thoroughly fucking devastated.
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For experts, GenAI assisted software development is a superpower. The screenshot shows what happens when Alexey, @ClickHouseDB CTO went all in with it. You'd rightfully argue commits/time say nothing about all the other metrics. But just check what that expert is doing at CH..
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Brig v0.3 is out brig.sh Headliner is Linux rootless support. On Linux #Brig now sets up the whole runtime incl. the VMM & guest kernels. MacOS already supported an end-to-end experience: upgrade with; brew upgrade --cask brig
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Also, kudos to Peyton Kennedy of @EndorLabs for responsibly disclosing a CWE-59 symlink path traversal Expl. scenario required an agent planting a symlink dir in a shared volume in guest, and then another run of Brig mounting the planted symlink to get r-w access. Fixed in v0.3
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We’d love your feedback, including appsec attacks, threat model questions, and bug reports!
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Panagiotis Moustafellos retweeted
We’ll be at Open Hackathon this Friday, Sept 25, as a Silver Sponsor. Come by the NOFire AI booth at Zone01, Nea Ionia. Meet the team and tell us what you’re building.
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Panagiotis Moustafellos retweeted
thoughts on Typesafe/Jev: I'm surprised that a general-purpose classifier (or discriminative model) can be just as interesting to the public as a general-purpose generative model. I've worked on search and discriminative models for years, so maybe I should have called this upfront, tbf I never thought about making them general-purpose beyond search. Typesafe also positions Jev really well as "System 1", a complement to the generative models we already have. Humble, unassuming, and sidestepping the frontier-lab warzone. Jev's success could be disruptive to today's agentic systems in many ways, such as tool-calling and routing patterns. Over the last three years the consensus was to use a small generative model for routing, tool calling, MCP etc. Time to pause and rethink such architecture, because we'll probably see tool calling and routing move back to discriminative models. Whoever ships the next Jev-like open-weight base model will likely win the community.
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Jev (RLCD) opens exciting opportunities. A general purpose classifier is what many usecases are after. LLMs are the wrong or expensive choice for many of the problems they are used for today. Top open Qs? Training data set, what is it? shape/origin? How's the model eval'ed?
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We built Brig as part of @NOFireAI's work on controlled autonomy in production. We’ve open-sourced the #sandbox so developers can use the same microVM isolation for coding agents on Mac and Linux. All components Apache 2.0.
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Stop debating; It's pronounced OmaRCE #omarchy
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Panagiotis Moustafellos retweeted
This is true. It wasn't actually possible before 2010 because datacenter networks would bottleneck. We used to design coupled storage/compute where you brought compute close to "big data". But research on "full bisection bandwidth" networks made it possible to essentially just talk from any machine to the storage system at full speed. The disaggregation started then! Databricks and Snowflake started soon after many others followed. Now "Put it on the object store" is the way to go.
"Put it on the object store" remains undefeated. - OLAP: Lakehouse - OLTP: Lakebase - Kafka: Warpstream - Vector Search: Turbopuffer - Git: Cursor Origin
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While working on Ravel we noticed arrayef getting yanked, see: github.com/NOFireAI/ravel/co…, decided to keep the 0.3.9 pin. Now assessing. This is why we develop in our #sandbox solution. We are soon announcing the FOSS release of our sandboxing solution to the public. Stay tuned.
‼️Two popular Rust crates, arrayref and append-only-vec, were compromised in a supply chain attack. arrayref alone has 244M downloads. The malware ran at build time, which means anyone who compiled a project that pulled one in was hit, without ever calling the crate. Here's the breakdown 🧵
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