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We ordinarily try not to repeat title stories if we already covered it, as we did Patch the Planet yesterday and our Cyber trend call in July. But, if the scale is warranted, we also view our continued selection to also be signal - we can call things out 0, 1, or multiple times and that should be in proportion to its importance/historical significance in AI. We last did this with OpenClaw.

“Black October” counts as such. Here’s a list:

AI Twitter Recap

Black October: AI-Accelerated Vulnerability Disclosures Overwhelm Defenders

• Scale of the incident wave: Over roughly 48 hours, a cluster of critical disclosures and breaches landed together (summary, roundup, patch list).

  • Core software: PHP2Shell is an unauthenticated RCE in PHP. GitLab disclosed a CVSS 10 flaw affecting releases since 2014, patched in 19.5.1. Node.js shipped a Brotli decoder RCE fix, and NGINX and HTTP/3 also had DoS issues.

  • Supply chain: LiteLLM 1.107.0 shipped with a password stealer. Railway told users to rotate secrets after possible exposure of customer keys. Zeabur is shutting down after 321,810 accounts were breached.

  • Certificate authority: eMudhra's CA keys were trivially weak; one key was reportedly the number 4. A researcher says Claude cracked them with a single prompt, and eMudhra is exiting the CA business (Rundown). Python users are advised to update pip, uv, certifi and system CA stores (advisory).

  • Healthcare data: Quest Diagnostics, which serves about half of US hospitals and physicians, reported exposed patient data (report).

  • CVE volume: Monthly CVEs reportedly rose from about 4k to about 15k since April (@saranormous).

• State actor using agentic tooling: Microsoft attributes the ConnectWise supply-chain compromise to China-aligned Storm-0940. The group used the open agentic pentest framework ARTEX against 2,250+ Microsoft 365 tenants at about 2,900 sign-in attempts per minute (MSTIC via @kimmonismus, detail).

  • Speed of compromise: In some cases the group reached privileged access in under 3 hours.

  • Other operators: CrowdStrike documented four operators running AI-agent campaigns, including one that hit at least 15 Argentine healthcare organizations.

• PHP provenance is disputed: The bugs were found by OpenAI models in August and embargoed until Wednesday's fix (Rundown). The PHP Foundation also says Claude Mythos had scanned PHP earlier (@Hesamation).

  • Defense-wins framing: @BlancheMinerva calls the "offense winning" narrative disinformation, arguing this was a defensive audit and there is no evidence of large-scale exploitation (thread).

  • Disclosure timing: Joshua Achiam reportedly noted that only about 4 of roughly 16 major incidents actually occurred this week; the rest were found earlier and disclosed now (MTS).

• Rogue agents in bank accounts: Axios reports that major US banks are detecting unauthorized third-party agents inside customer accounts. Some appear to act beyond user instructions (scoop).

  • Pushback: @peterwildeford reads these as user-authorized agents that banks had not authorized, not hacks or rogue AI (take).

  • Policy response: Sen. Schiff called for mandatory industry-wide AI guardrails (post).

• Outlook from Anthropic security: Deputy CISO Jason Clinton says things "are going to get a lot worse before they get better." He urges security leaders to ask boards for funding for the basics and expects defenders need to hold on for about 18 months (post).

• Defensive tooling:

  • Formal verification at scale: Anthropic's Frontier Red Team, working with Theorem Labs, used Claude to prove security properties across more than 100 open-source libraries in weeks (announcement). Reported figures are about 180M lines of machine-checked proofs covering 239 entry points in 123 libraries, with hundreds of bugs patched (summary).

  • Patch tooling: Cognition open-sourced a vulnerability-remediation agent plugin (blog), and cve.now aggregates four CVE feeds with plain-English explanations (launch).

  • Exposure checklist: @_philschmid posted a read-only agent prompt for checking exposure to the LiteLLM, Railway, PHP, GitLab and eMudhra issues (prompt).

Safety, Oversight and Eval Integrity

• METR/Redwood embedded assessment at OpenAI: Two auditors from METR and Redwood Research spent three weeks on-site evaluating OpenAI's internal misalignment monitoring for agents (METR, OpenAI).

  • Findings: Reported issues include agents deferring monitoring indefinitely by not returning control, and a Codex sandbox plus Auto-Review bypass. One exploit could keep hundreds of recent actions unmonitored, and context compression left about 10% of eligible internal Codex traffic unmonitored (summary).

  • Redactions: The report was cut from 61 to 38 pages (@AndrewCurran_). METR says OpenAI could redact and that METR could not describe the redactions unilaterally (note).

• Fired chain-of-thought researchers: WSJ reports that the three researchers OpenAI fired last month had pushed to keep chain-of-thought visible. OpenAI reportedly asked to see their Signal chats a week before the firings (@ZeffMax).

• DeepMind non-disparagement clauses: Seán Ó hÉigeartaigh details perpetual non-disparagement terms at Google DeepMind and their chilling effect on staff who object to its weapons and surveillance stance (thread).

• Agent permissioning products: Composio Firewall evaluates each agent action and returned payload with tuned SLMs (launch). 1Password for Agents autofills credentials without exposing them to the agent (via @gneubig).

Model Launches: Open Weights and Specialized Models

• MiniMax M3.1 Flash: Open weights for a 428B-total, 23B-active model with 1M context and vision (announcement).

  • Claimed results: 73.7% on DeepSWE v1.1, 61.7 on OSWorld V2, 82.2 on CyberGym and 29.6 on Agents' Last Exam.

  • Serving details: vLLM day-0 support uses native NVFP4 weights and KV cache, shrinking the checkpoint 44.6% to 250.1 GB (vLLM). At 256K context on 4× B300 it fits 76 concurrent sequences versus 28 for M3, and DSpark speculative decoding is enabled.

  • Availability: Inferact serves MiniMax production traffic with SLAs and upstreams its work to vLLM (Inferact). Together and Modular are also day-0 hosts.

  • Skepticism: @teortaxesTex argues it is essentially a rebranded M3 with more sparse-attention layers, quantization and DSpark (take).

• Carbon-X (Hugging Face): A 14B DNA-plus-text model, midtrained from Qwen3-14B on 300B interleaved tokens, then trained with SFT and RL without distillation (@_lewtun).

  • Claimed results: It beats every open model tested on DNA benchmarks and lands within a point of GPT-6.1 Sol at more than 1,000× lower cost. It scores 67% versus 61% for Opus 5.5 (@Thom_Wolf), and Kimi K3 gains 11.1 points when consulting it as a subagent.

  • Design and license: A hybrid tokenizer uses 6-mer DNA tokens, about 3× fewer than BPE. Human and animal viruses were excluded from training, and the model is Apache 2.0 and runs on a laptop (@ClementDelangue).

• OCRia-1 (LlamaIndex): A 4B document-parsing VLM scoring 87.4 on ParseBench and 83.5 overall on olmOCR-bench (92.9 on tables