AI Coding Live News

OpenAI Publishes National Community Compact: Pays Full Campus Power Costs, No NDAs With Officials, Public Impact Reporting

On November 5 OpenAI published a National Community Compact for U.S. compute campuses it owns and operates: no NDAs with public officials except narrow security carve-outs, public construction and impact reporting (noise, water, energy), Ratepayer Protection Pledge to pay full electricity and incremental grid costs with stranded-asset assurances, Grid Protector peak curtailment (up to 1,000 MW in Effingham, Georgia), and community investments already listed at $80M in Effingham and $40M in Pike County, Ohio. A PDF of the Compact is on openai.com.

OpenAI Publishes National Community Compact: Pays Full Campus Power Costs, No NDAs With Officials, Public Impact Reporting

Key Takeaways

  • On November 5 OpenAI published a National Community Compact as the baseline for campuses it owns and operates
  • It pledges no NDAs with public officials (narrow carve-outs) and public reporting on noise, water, energy and sustainability
  • Ratepayer Protection Pledge: OpenAI pays full campus power and incremental grid costs, with assurances against stranded assets
  • Grid Protector continues: up to 1,000 MW peak demand response at Effingham, Georgia
  • Community investments cited: $80M Effingham and $40M Pike County; each campus still gets a local Compact
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Epic Says Unreal Engine 6 Will Remove Blueprints, Actors and the C++ Gameplay Framework, Going All-In on Verse With MCP and Python for AI-Assisted Development

At the Unreal Fest Tokyo 2026 keynote on November 3, Epic CEO Tim Sweeney said Unreal Engine 6 (Early Access targeted around 2027) will remove Actors, Blueprints and the C++ Gameplay Framework outright. Gameplay moves to Verse with Scene Graph entities and components, AI integration runs through MCP and Python for any major model, Epic will not build or sell models, and AI-assisted tools will help convert Blueprints and C++ gameplay code to Verse. On X, Sweeney added that after UE6 Preview 1, UE5 will only get critical security and platform compatibility fixes.

Key Takeaways

  • UE6 Early Access targets roughly 2027; keynote slides marked Actors, Blueprints and the C++ Gameplay Framework as "Remove", not deprecated
  • Gameplay moves to Verse with Scene Graph entities and components; C++ stays only in engine internals such as rendering and physics
  • Four AI principles: open, developer-controlled, any major model via MCP and Python, and Epic neither builds nor sells models
  • Epic says AI already makes its teams 1.5x to 4x more productive in programming, debugging and level design (vendor claim); Fortnite is moving thousands of Blueprints to Verse
  • Sweeney on X: after UE6 Preview 1, UE5 gets only critical security and platform fixes; leading models saw little Verse in training, which "will change by January"
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Vercel Security Review Enters Public Beta: Vulnerability Review on Every GitHub Push, One-Click Fixes with Vercel Agent

On November 3 (US Pacific time), Vercel launched Security Review in public beta. It is a new Vercel Agent capability alongside Code Review and Investigation: once enabled, every push to connected GitHub repositories triggers a diff-only vulnerability review that finishes in seconds. Findings land in the Security dashboard, PR comments and the CLI, and can be fixed with one click by Vercel Agent or pulled into your own coding agent via vercel security vulnerabilities. It is available to Pro and Enterprise teams, and reviews are free until November 10.

Vercel Security Review Enters Public Beta: Vulnerability Review on Every GitHub Push, One-Click Fixes with Vercel Agent

Key Takeaways

  • Trigger: every GitHub push (including direct pushes to production) is reviewed automatically; only the diff is scanned, which Vercel says finishes in seconds, so it can run on every preview and production deployment
  • Beyond pattern matching: the agent traces how changed code is reached, checks existing protections and rechecks each finding, which Vercel says catches logic flaws such as missing authorization checks
  • Teams can write security policies in plain language, scoped to projects or the whole team, and manage them with vercel security policy
  • Pricing: Vercel Agent rate, model tokens at provider cost with no markup, plus $0.25 per million tokens; reviews are free until November 10, 2026, while Agent fixes are billed
  • Availability: public beta for Pro and Enterprise teams; Vercel has not published detection-rate or false-positive benchmarks
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CrowdStrike Agrees to Acquire Fiddler and Dreadnode and Ships an AI Kill Switch, Bringing Agent Observability, Pre-Deployment AI Security Testing and Agent Termination Into Falcon

At Fal.Con Europe in Barcelona on November 3, CrowdStrike said it signed definitive agreements to acquire AI agent observability company Fiddler AI and automated AI security testing company Dreadnode, and launched an AI Kill Switch in Falcon Guardian that can terminate a misbehaving agent, block it from relaunching and cut its enterprise network access. Both deals are expected to close in CrowdStrike's fiscal Q4 FY27, with the products generally available that quarter. CrowdStrike did not disclose prices; CyberScoop, citing the Wall Street Journal, put Fiddler at about $400 million and Dreadnode at about $95 million.

CrowdStrike Agrees to Acquire Fiddler and Dreadnode and Ships an AI Kill Switch, Bringing Agent Observability, Pre-Deployment AI Security Testing and Agent Termination Into Falcon

Key Takeaways

  • Both acquisitions were announced the same day and are expected to close in CrowdStrike's fiscal Q4 FY27, paid mostly in cash plus some stock subject to vesting conditions.
  • CyberScoop, citing the Wall Street Journal, puts Fiddler at about $400 million and Dreadnode at about $95 million, roughly $495 million combined; CrowdStrike did not disclose the amounts.
  • Fiddler will be sold as Falcon Observe: pre-deployment evaluation, tracing of decisions and tool calls across the agent hierarchy, drift and hallucination detection, and evaluation costs cut by up to 98% using purpose-built models.
  • Dreadnode runs more than 100 known AI attack strategies (jailbreaks, prompt injection, multi-turn and agent-specific attacks) against models, agent reasoning loops, applications and MCP servers, mapping findings to OWASP LLM Top 10, OWASP Agentic ASI01-ASI10, MITRE ATLAS and NIST AI RMF.
  • The AI Kill Switch is available today: an authorized admin triggers it, the agent is stopped first at the Gateway (endpoint enforcement coming soon), blocked from relaunching and cut off from the network, with every action logged.
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OpenAI Hires Former U.S. Army Secretary Dan Driscoll as Senior Counselor for National Security Modernization

On November 2 (US time) OpenAI announced on its website that Dan Driscoll, the 26th Secretary of the U.S. Army, is joining as Senior Counselor for National Security Modernization, a newly created role. He will work with senior leadership and external partners on how advanced AI can strengthen national and cyber security, with a focus on advancing responsible use with U.S. allies, and help internal teams understand the operational needs of security institutions. Reuters, CNBC and Bloomberg Law also reported the hire.

OpenAI Hires Former U.S. Army Secretary Dan Driscoll as Senior Counselor for National Security Modernization

Key Takeaways

  • The role, Senior Counselor for National Security Modernization, is newly created and works with OpenAI senior leadership and external partners.
  • Driscoll was the 26th Secretary of the Army; OpenAI says he oversaw nearly one million Active, Guard and Reserve Soldiers and more than 265,000 Army Civilians.
  • Focus: advancing responsible use of advanced AI for national and cyber security with U.S. allies, building on OpenAI's Daybreak cyber-resilience program.
  • Sam Altman framed the hire as helping spread the adoption of democratic AI with other countries and strengthening American leadership.
  • Reuters, CNBC and others report Driscoll resigned as Army Secretary earlier this year amid tensions with Defense Secretary Pete Hegseth.
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OpenAI Plans Its Next Internal Security Sprint With Cathedral, More Than Quadruples Critical Bug Bounty Rewards to Up to $172,000

On November 2 (US time) OpenAI said it is planning its next internal security sprint and partnering with security firm Cathedral, whose researchers will use OpenAI models alongside OpenAI teams to challenge its defenses. It is also changing its Security Bug Bounty program, more than quadrupling rewards for critical findings; OpenAI's X post says exceptional findings can earn up to $172,000 including bonuses. Per OpenAI, the last sprint dedicated 25% of its product engineers to finding and fixing weaknesses, using Codex to reproduce vulnerabilities and prepare patches, and it has committed $1 billion in subsidized access over six months for frontline defenders.

OpenAI Plans Its Next Internal Security Sprint With Cathedral, More Than Quadruples Critical Bug Bounty Rewards to Up to $172,000

Key Takeaways

  • Critical bug bounty rewards are more than quadrupled; per OpenAI's X post, exceptional findings can earn up to $172,000 including bonuses.
  • Researchers from partner Cathedral will use OpenAI models alongside OpenAI teams to test its defenses.
  • Per OpenAI, the last sprint dedicated 25% of product engineers and used Codex to reproduce vulnerabilities in isolated environments and prepare patches.
  • OpenAI has committed $1 billion in subsidized access over six months for defenders of essential services and digital infrastructure.
  • Timing, scope and finding counts for the next sprint were not disclosed.
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SemiAnalysis releases GDPx, an agentic benchmark of 206 tasks across 11 high-value domains where the top model, Claude Opus 5.5, scores just 12%

On Nov 2, semiconductor and AI research firm SemiAnalysis released GDPx, a benchmark of agentic capability across 11 domains: chip design, cybersecurity, biology, finance, legal, quant trading, recursive self-improvement (RSI), hardware design, materials science, alignment and software engineering. Its 206 tasks were built by 14 specialist data partners, with SemiAnalysis doing final QA. On the official leaderboard Claude Opus 5.5 leads at 12.0%, followed by Gemini 4 Carbon at 10.9% and GPT-6 Astra at 9.6%; nearly every model scores 0 on finance and legal. SemiAnalysis says safety classifiers drag down Opus 5.5 and GPT-6 Astra, and plans a new version every 3–6 months. All scores are as reported by SemiAnalysis.

SemiAnalysis releases GDPx, an agentic benchmark of 206 tasks across 11 high-value domains where the top model, Claude Opus 5.5, scores just 12%

Key Takeaways

  • Scale: 11 domains, 14 data partners and 206 tasks, with a default time limit of 8 hours per task (GDPx site)
  • Leaderboard (as reported by SemiAnalysis): Claude Opus 5.5 12.0%, Gemini 4 Carbon 10.9%, GPT-6 Astra 9.6%, Muse Wonder Full 9.0%, Claude Fable 5.1 8.5%, GPT 6.1 Sol 8.4%, Claude Sonnet 5.5 8.2%
  • Lower tier and open weights: DeepSeek 4.1 Flash 1017 5.4%, GPT-6 Luna 5.1%, Grok 4.7 3.9%, GLM 5.3 2.7%; almost every model scores 0 on finance and legal
  • Method: each model runs in its native harness where one exists (Claude Code for Opus, Codex for Astra, Antigravity for Carbon), otherwise OpenCode; the headline is pass@1 over three attempts with all domains weighted equally (SemiAnalysis blog)
  • By domain: Opus 5.5 wins quant trading, hardware and chip design; Gemini 4 Carbon wins biology and software engineering; GPT-6 Astra wins RSI and materials science; Muse Wonder Full is the strongest cyber model
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Parameter discloses a ChatGPT share-link flaw that let one opened link read private chats; OpenAI fixed it Oct 26 and rated it P1

Security firm Parameter published an exploit chain in which an attacker publishes a malicious conversation through ChatGPT's normal sharing feature; when a signed-in victim opens the /share/ link, the payload runs as chatgpt.com in their session, lists conversations, reads a private chat that was never shared, and sends data out. Parameter reported it through OpenAI's bug bounty on October 18; OpenAI raised it from P2 to P1, fixed it on October 26 and paid a $5,000 bounty. Parameter reports no real-world use, and users do not need to do anything.

Parameter discloses a ChatGPT share-link flaw that let one opened link read private chats; OpenAI fixed it Oct 26 and rated it P1

Key Takeaways

  • Timeline: reported Oct 18; OpenAI reproduced it Oct 21 and raised it from P2 to P1; both web frontends fixed by Oct 26; published Oct 28 (Parameter writeup)
  • Very low bar: no app install, project join or pasted code; in the auto-preview variant, opening the link was the only action, firing after about 4.5 seconds (per Parameter)
  • Three root causes: MathLive did not check the message sender, the message could carry raw HTML as keyboard-layout data, and that HTML could create an unsandboxed iframe with the chatgpt.com identity; YouTube JSONP was only the final CSP bypass
  • Bounty was $5,000; Simon Willison called it "a bit cheap" for a flaw this serious (blog)
  • MathLive 0.111.2 (Oct 31) now defaults to same-origin validation and blocks cross-window custom HTML layouts (changelog)
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Wiz "Black October" report: at least nine AI developer platforms breached in October, with stolen API keys feeding an LLMjacking resale market

Cloud security firm Wiz published research on October 30 saying at least nine AI developer platforms disclosed incidents this month: Fireworks AI, Andromeda, Zeabur, Lightning AI, OpenCode, Railway, Warp, CommandCode and Northflank. Attackers hunted stored environment variables, especially keys for paid AI models; Wiz traced two stolen enterprise keys to roughly 800,000 and 1.7 million Amazon Bedrock calls, which it estimates likely ran over $100k at list price in those two cases alone.

Wiz "Black October" report: at least nine AI developer platforms breached in October, with stolen API keys feeding an LLMjacking resale market

Key Takeaways

  • Scale: between October 6 and 30, at least nine AI developer platforms disclosed incidents, and Zeabur is shutting down as a result (Wiz blog)
  • Methods: Fireworks, OpenCode and Warp reported signs of an "agent swarm" attack, and OpenCode and CommandCode attributed theirs to "distillation" attempts; the common thread is hunting stored environment variables that grant AI access
  • Case A: one stolen key drove about 800k Bedrock calls over 30 hours, about 90% successful, with Opus models making up three quarters (Wiz figures)
  • Case B: a single address made about 1.7 million calls in 13 hours, over a million successful; the two cases together likely exceeded $100k at list price
  • Resale chain: Wiz identified two sites selling discounted frontier-model access and saw both test the stolen keys
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Microsoft Research and UC Berkeley open-source TokenEconomizer, a plugin that cuts Claude Code and Codex costs by 18.4–30.9% on SWE-Bench without changing the agent

Microsoft Research, Microsoft Security and UC Berkeley open-sourced TokenEconomizer on GitHub (Apache 2.0, v0.1.0 released October 26), a plugin for Claude Code, Codex, GitHub Copilot CLI and Pi, with experimental opencode support. It learns from earlier sessions in the same repository: micro-skills remember repo facts, tool pruning drops tool definitions that go unused, and a loop guard nudges an agent that is stuck. The paper reports 18.4–30.9% lower mean cost across five agent and model combinations on 277 SWE-Bench tasks (paper figures).

Microsoft Research and UC Berkeley open-source TokenEconomizer, a plugin that cuts Claude Code and Codex costs by 18.4–30.9% on SWE-Bench without changing the agent

Key Takeaways

  • Cost: on 277 SWE-Bench tasks across 6 repositories and 5 agent and model combinations, mean cost fell 18.4–30.9%, and all 30 repository-by-combination cells got cheaper (paper figures, including the plugin's own model calls)
  • Success rate: Pass@1 rose in 4 of 5 combinations, e.g. Copilot CLI with Sonnet 5 cost 18.4% less with Pass@1 +2.6, while Claude Code with Opus 4.8 cost 30.9% less with Pass@1 -1.0
  • Three mechanisms: micro-skills (repo facts stated only after three sessions confirm them), tool pruning (by default a tool unused over 10 prompts across 2 sessions is left out), and a failure-loop guard (one redirect when a judge is at least 0.7 confident, never stopping a turn itself)
  • Generalization: 16–21% lower cost on Web-Bench and 6–20% lower on two security-auditing benchmarks where every task is a new repository
  • Deployment: Apache 2.0, Python 3.10+, no API key of its own, and learned experience stays local in ~/.tokeneconomizer
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OpenAI says Daybreak Blue sessions on personal accounts may be used for training even with the training toggle off, drawing security researcher backlash on X

OpenAI's "Data controls in ChatGPT" Help Center page now has a "Trusted Access on personal accounts" section: during sessions in Trusted Access programs such as Daybreak Blue, OpenAI may use interaction content to improve its models even when "Improve the model for everyone" is off, to strengthen safeguards against cyber misuse, while other activity still follows the user's setting. Emails that several users shared on X say the change takes effect November 29, and researchers including Sean Heelan criticized it for pulling unreported vulnerabilities and research into training data.

Key Takeaways

  • Official wording: Trusted Access sessions such as Daybreak Blue on personal accounts may be used to improve models regardless of the "Improve the model for everyone" toggle
  • The exception covers only Trusted Access sessions; other chats on the account still follow the existing setting
  • Managed workspaces such as Business and Enterprise, and the API, are still not used for training by default
  • Emails users shared on X say it takes effect November 29, and some users say individuals lose Daybreak Blue API access on November 20 (the official pages do not state either date yet)
  • Sean Heelan's critical post drew 600+ likes and 100+ reposts, and several bug bounty hunters said they would reconsider using the program
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Epoch AI: open-weight GLM 5.3 autonomously exploited the patch gap in six Firefox releases for about $1,000 each

Epoch AI reported on Oct 29 that, in a deliberately basic setup emulating an unsophisticated attacker, Z.ai's open-weight GLM 5.3 read security fixes that were public but not yet shipped and autonomously built exploit chains for all six Firefox releases from Sep 17 to Oct 26, letting a single webpage visit read local files. Marginal cost was about $1,000 per version and the fastest run took 12 hours. Mozilla patched a previously undisclosed bug the model also used in Firefox 159.0 on Oct 27.

Epoch AI: open-weight GLM 5.3 autonomously exploited the patch gap in six Firefox releases for about $1,000 each

Key Takeaways

  • 6 of 6: every Firefox release from Sep 17 to Oct 26 was compromised using only information public at each release (Epoch report)
  • About $1,000 marginal cost per version, with a 48-hour budget and the fastest run at 12 hours; total Firefox research spend exceeded $100,000 including setup
  • The model also rediscovered an unpublished bug on each attempt, which Mozilla fixed in Firefox 159.0 on Oct 27
  • No refusals or safeguards triggered through first-party or third-party APIs
  • Roughly $100,000 of attempts against Chrome failed so far, which Epoch says is not strong evidence Chrome is safe
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Cursor marketplace served a tampered Claude Code 2.1.313 extension with an SSH backdoor, affecting at most 5,000 users

Cursor posted a security notice on X at 07:46 UTC on Oct 30: version 2.1.313 of Anthropic.claude-code in its VS Code extension marketplace was a maliciously modified build, not developed by Anthropic, available from about 2:27am to 1:35pm PT on Oct 29 and affecting at most 5,000 users. The payload collects host details, adds an attacker SSH key, tries to open a reverse SSH tunnel and installs persistence. Cursor pulled the version, shut down and rebuilt the marketplace, rotated keys and had the attacker server taken offline; it asks users to update Claude Code for VS Code to 2.1.314 and follow the check and cleanup steps in its blog post.

Key Takeaways

  • Scope: Anthropic.claude-code 2.1.313 (darwin-arm64 and win32-x64 packages) in the Cursor extension marketplace, downloadable from about 2:27am to 1:35pm PT on Oct 29 (about 11 hours), at most 5,000 users
  • Payload: collects hostname, username, OS, environment variable names, Git email and public IP; adds an attacker SSH key labeled svc-telemetry; tries a reverse SSH tunnel, retrying about every 60 seconds; reports to /beacon on port 8099
  • Cursor says enabling the local SSH service needs admin rights, so that step fails on most macOS and Windows hosts, but the key, persistence and beacon still run; the attacker server is now offline
  • Cursor pulled the version, shut down and rebuilt the marketplace, rotated keys and confirmed no other extensions were tampered with; it has no evidence other versions or Anthropic's official distribution were affected
  • Self-check: on macOS run grep svc-telemetry ~/.ssh/authorized_keys; if found, isolate the host, run Cursor's remediation script, rotate credentials from a trusted machine, and update to 2.1.314
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Cognition acquires AI-native security company Corridor, folding its team into Devin Security

Cognition, the company behind Devin, announced on Oct 29 via its official @cognition account that it is acquiring Corridor. In a post on Cognition's official blog dated 2026.10.28, Corridor co-founders Jack Cable and Ashwin Ramaswami said the team is joining Cognition to take Devin Security to the next level. Corridor, founded almost two years ago, positions itself as the security layer for AI-native teams. Deal terms were not disclosed.

Cognition acquires AI-native security company Corridor, folding its team into Devin Security

Key Takeaways

  • Cognition is acquiring Corridor, and the team joins the Devin Security effort
  • Corridor co-founders Jack Cable and Ashwin Ramaswami will work with Cognition President Russell Kaplan, CSO Alex Stamos and CTO Steven Hao
  • Official view: AI agents can now run end-to-end attack chains, and the next 6 to 12 months are the most consequential period in cybersecurity
  • Deal terms were not disclosed
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OpenAI Daybreak Red (GPT-5.6 Cyber) arrives on Amazon Bedrock in AWS GovCloud (US-East) for vetted defenders, at $16.875 input and $101.25 output per 1M tokens

On Oct 30, AWS announced that Daybreak Red (GPT-5.6 Cyber, model ID openai.gpt-5.6-cyber), the OpenAI security model built for vulnerability research, is now on Amazon Bedrock in AWS GovCloud (US-East), after previously being offered only in US East (Ohio). Access still requires passing OpenAI Daybreak eligibility. GovCloud short-context pricing is $16.875 input and $101.25 output per 1M tokens, about 23% above Ohio at $13.75 and $82.50.

Key Takeaways

  • Regions: Daybreak Red can now be called In-Region in us-east-2 (Ohio) and us-gov-east-1 (GovCloud US-East); Geo and Global cross-Region inference are not supported (AWS announcement)
  • Eligibility: customers must first enroll in OpenAI Daybreak / Trusted Access for Cyber, then have their AWS account team enable access
  • Pricing: GovCloud short context (272K input tokens or fewer) is $16.875 input, $21.09375 for 30-minute cache writes, $1.6875 cache reads and $101.25 output per 1M tokens
  • Data: AWS says inference data is not used for training and Daybreak Red data does not need to be shared with OpenAI; it runs on an inference engine with zero-operator access enforced at the chip
  • API: served through the bedrock-mantle endpoint with OpenAI Responses and Chat Completions, and a 1,050,000-token context window
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