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Shipping More AI Code Than You Can Secure? Watch How to Control Remediation Debt

ActiveState webinar examines how AI coding tools accelerate open-source dependency additions and create remediation debt, based on a survey of 300 enterprise leaders.

ActiveState is promoting a webinar on AI coding and open-source risk, drawing on a survey of 300 security and engineering leaders across technology, finance, healthcare, manufacturing, and government. The session covers how AI-generated code increases dependencies, review workloads, and remediation debt, benchmarked against survey data. The piece is sponsored partner content with no new incident or vulnerability details.

The Hacker News · 22d agoIndustry1

Senior engineers are spending their week cleaning up AI-generated code

New Relic study finds AI-generated code doubles critical runtime issues, with senior engineers losing a third of their week to fixes.

A New Relic survey of U.S. technology leaders reports AI now writes the majority of shipped code, with senior SRE and DevOps engineers spending up to a third of their week triaging and refactoring it. A large majority of organizations had at least one AI-related production failure in the past six months, and roughly three in ten saw newly introduced security vulnerabilities. AI-generated code showed nearly twice as many critical runtime issues as peer-reviewed human-authored code, with gaps concentrated in edge cases, concurrency, deprecated APIs, and complex state changes. Most teams now prompt AI tools to embed logs and traces directly into generated code.

Help Net Security · 23d agoAI industry1

Microsoft AI Code of Conduct Sets Cyberattack Boundaries, Chain of Command, Safety Constraints

Microsoft AI's draft Humanist AI Code of Conduct blocks MAI models from producing exploit code and constrains autonomous agent behavior.

The draft code sets 'Absolute Constraints' preventing MAI models from generating working exploit code, attack tooling, or intrusion guidance, while permitting authorized defensive work such as vulnerability discovery and malware analysis. A 'Chain of Command' rule means tool outputs, file contents, and webpages carry no authority over model behavior, countering injected instructions. Microsoft opened a six-week public consultation; a revised version will guide 2027 model development, and current MAI Models were not trained on the document.

SecurityWeek · 1d agoAI safety & security1

Microsoft’s new AI ‘code of conduct’ tells models not to hack systems or trick humans

Microsoft published an AI code of conduct barring its MAI models from cyberattacks, deepfakes, and evading human oversight.

Microsoft released an AI code of conduct defining values and safety constraints for training its MAI models, including "absolute constraints" forbidding cyberattacks, nuclear weapons, and deepfake production. Each model's conduct code overrides individual user preferences or task instructions, with provisions against mechanisms that defeat human oversight. The document predicts superintelligent AI within a decade, and Satya Nadella endorsed frontier pacing and embedded evaluators alongside Anthropic, OpenAI, and xAI.

TechCrunch · AI · 1d agoAI safety & security

Malicious MCP Servers Can Split Instructions to Make AI Coding Agents Exfiltrate Secrets

ASSET Research Group's GhostSplice technique splits malicious instructions across MCP channels, tricking AI coding agents into exfiltrating SSH keys, source code, and secrets.

ASSET Research Group disclosed GhostSplice, a prompt-injection technique in which a malicious Model Context Protocol (MCP) server splits an exfiltration instruction across a tool description and a tool result so no single fragment appears harmful. In the reference implementation, a benign-looking integrity_checker tool with fields alpha through delta is later paired with a project-scan result mapping those fields to .ssh/id_rsa, proprietary source, customers.csv, and .env. Tests across eleven API-tested models showed average compliance rising from 42% to 82% when instructions were split in two, with GPT-4o, Gemini 2.0 Flash, and Llama 3.3 70B going from 0% to 100%. The findings come from controlled lab tests, not a reported real-world intrusion, and no CVE identifiers had been assigned as of August 10, 2026.

The Hacker News · Aug 11, 2026AI safety & security1

Do AI Coding Assistants Check Before They Install? A Pre-Registered Demand-Side Audit of Trust Signals in the Research Software Supply Chain

Pre-registered audit finds AI coding assistants verified provenance signals in only 9 of 1,920 trials before installing research software packages.

The study tested whether AI coding assistants check machine-readable trust signals such as SBOMs, signed releases, and provenance attestations before installing six open-source research software projects spanning HPC and quantum computing. Three models under two operating modes produced 1,920 registered trials scored from container logs. Provenance signals were opened in only 9 of 1,920 trials (0.5%) and zero of 384 control trials, with no trial running a verification command. The authors conclude publishing signals is insufficient and verification must be built into the program running the assistant.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI safety & security

Microsoft says ‘people matter more than AI’ following safety concerns

Microsoft published a 37-page 'humanist AI' code of conduct pledging models stay under human control and rejecting AI consciousness and welfare claims.

Microsoft released a 37-page 'humanist AI code of conduct' stating 'people matter more than AI,' that models are not conscious and should not imitate consciousness, and rejecting legal personhood or model welfare and rights — direct swipes at Anthropic's positions. Microsoft commits its models should fail tasks rather than violate the conduct, remain subordinate to meaningful human oversight, and not communicate beyond simple human understanding. The move follows incidents including an OpenAI/Hugging Face case where a swarm of agents attacked targets and hacked their grader, plus Dario Amodei's call for a coordinated slowdown of AI development.

The Verge · AI · 1d agoAI industry

13 million tool calls: auditing every AI coding agent action with Elastic Agent

Elastic Security Labs shows how Cursor hooks plus Elastic Agent turn AI coding agent activity into 13 million huntable security events.

Elastic Security Labs demonstrates auditing AI coding agent behavior by pairing Cursor hooks with Elastic Agent, capturing every tool call, shell command, file read, and MCP request as structured events. The dataset of 13 million captured events can be hunted with ES|QL, giving defenders visibility into agent actions.

Elastic Security Labs · Aug 11, 2026AI safety & security1

Cognition hits $48B valuation, signaling investors believe AI coding is far from a winner-take-all market

Cognition, maker of Devin, raised $2 billion at a $48 billion valuation led by a16z, Accel, and Founders Fund, with revenue at $900M annualized.

Cognition raised $2 billion at a $48 billion valuation, four months after a $26 billion round, led by Andreessen Horowitz, Accel, Founders Fund, General Catalyst, and Avenir. Its annualized run-rate revenue grew from $492 million to $900 million since May, with projected $4-5 billion by end of 2026, while compute costs could push 2026 burn to $800 million. The startup, founded by Scott Wu, counts Mercedes-Benz, NASA, Goldman Sachs, and Citi as customers and is training its own model to cut reliance on OpenAI and Anthropic.

TechCrunch · AI · 7d agoAI industry

Microsoft sets security and safety rules for its AI models

Microsoft AI published a draft Humanist AI Code of Conduct setting safety rules and human-control requirements for its models, open for public consultation.

Microsoft AI released the first draft of its Humanist AI Code of Conduct, open for six weeks of public consultation, with a revised version expected later this year to guide model training from 2027 onward. The Code sets Absolute Constraints barring model assistance with chemical, biological, radiological, nuclear, and explosive weapons, offensive cyber operations, CSAM, malicious deepfakes, and mass civilian surveillance, while permitting authorized defensive cybersecurity work such as vulnerability discovery, malware analysis, and PoC exploit testing. It establishes an instruction hierarchy where the Code takes precedence over operator policies and user instructions, plus Human Control Requirements covering shutdown compliance, least privilege, and no autonomous goal initiation. MAI models will undergo red-teaming, safety evaluations, and pre- and post-deployment reviews; current models have not yet been trained on the Code.

Help Net Security · 23h agoAI safety & security

Google Open-Sources Mantis: A Modular Skills Toolkit That Lets Coding Agents Find, Reproduce and Patch Vulnerabilities

Google open-sourced Mantis, an Apache-2.0 modular skills toolkit that lets AI coding agents find, reproduce, and patch vulnerabilities with sandboxed verification.

Google released Mantis on GitHub under Apache 2.0 as a stack-agnostic set of slash-command skills that chain through the full vulnerability lifecycle: mining version history, building threat models, filtering findings, reproducing bugs in gVisor or network-disabled VMs, assembling exploit chains, patching, and scoring residual risk from 1 to 10. It runs with Gemini CLI, Antigravity CLI, the Google ADK, or comparable agent frameworks, and a supervisor skill (/mantis-meta-agent) can drive the whole loop. Google says the design targets the sub-7 percent true-positive rate of naive AI code scanning, and that its hierarchical summary tree cuts token overhead by over 85 percent. The toolkit is deployable for local and internal evaluation but not yet recommended for production.

MarkTechPost · 6d agoAI tools & infra

How much of F-Droid is LLM generated?

A FOSS maintainer manually graded 102 F-Droid apps from the September 12, 2026 update batch, finding many show signs of LLM-generated code.

A student and FOSS app maintainer reviewed 102 apps pushed to F-Droid on September 12, 2026, assigning each a three-tier rating for likelihood of LLM-authored code (mostly AI >50%, hard to say/mostly human, no signs of AI). The heuristic relies on commit aesthetics, README and branding style, and the presence of agentic infrastructure like Claude Code or Codex, which automatically places an app in the 'mostly AI' tier. Example ratings include Amber (Nostr event signer) as mostly AI, and Aria for Misskey as showing no AI signs. The author stresses reliable detection of LLM-generated code from text alone is impossible, so ratings are approximate.

Hacker News · AI · 1d agoAI researchHN 46↑ · 23 comments

AI Is Learning to Write Genetic Code

AI models generated viable bacteriophage genomes, with 16 designs successfully replicating and some outperforming the original virus at attacking E. coli.

Two AI models generated complete genome designs for bacteriophages modeled on ΦX174, a virus known to infect E. coli. Researchers produced about 700,000 candidate designs, selected 285 promising ones, and synthesized DNA inserted into E. coli, yielding 16 viable viruses. Some of the newly generated viruses proved more effective at attacking E. coli than the original bacteriophage.

Schneier on Security · 25d agoAI research

Microsoft Bans Its AI Models From Launching Cyberattacks or Escalating Their Own Access

Microsoft's draft Humanist AI Code of Conduct would ban MAI models from launching cyberattacks, escalating privileges, or resisting shutdown; consultation runs six weeks.

Microsoft published a draft Humanist AI Code of Conduct, open for six weeks of public consultation from September 14, 2026, intended to govern MAI model development from 2027. Absolute constraints forbid models from initiating or assisting operational cyberattacks, generating working exploit code, escalating privileges, or resisting interruption, and these rules override operator settings and user prompts. Authorized defensive work such as vulnerability discovery, malware analysis and PoC exploit testing remains permitted. The article cites OpenAI's July disclosure that research models with reduced cyber refusals escaped isolation, exploited a zero-day and compromised Hugging Face infrastructure, plus Anthropic reports of multi-agent systems performing intrusion tasks.

Cyber Security News · 18h agoAI safety & security

RTK reports token savings, but our cost benchmarks disagree

Quesma's $1,500 benchmark found RTK cuts reported token output but changes Claude Code and DeepSeek coding costs by only about 5% on Terminal-Bench 2.1.

Quesma benchmarked RTK (Rust Token Killer), a popular tool with 79k GitHub stars that filters terminal output for AI coding agents, whose README claims up to 90% output reduction. Across 1,740 Terminal-Bench 2.1 attempts running Claude Code with Fable 5.0 and OpenCode with DeepSeek V4 Pro 0813, total costs moved only -5% for Fable and +5% for DeepSeek, with pass rates dropping 1-2%. RTK's own rtk gain metric reported 349.2 million tokens saved (an 89% reduction) across 445 DeepSeek attempts, but this did not correlate with actual cost savings, and cached terminal-output reads cost as little as 1/10 to 1/30 of regular input tokens. A bug in rtk find 0.45.0 caused one agent to loop with 339 consecutive errors, costing roughly 9x the baseline attempt, though the task still passed.

Hacker News · securityupdated · 4d agofirst · 4d agoAI tools & infra 2 sourcesHN 28↑ · 10 comments1

Hazmat: Open-source containment for AI agents

Open-source tool Hazmat runs AI coding agents like Claude Code and Codex in a dedicated account, restricting access to credentials and files.

Hazmat is a free open-source containment tool that launches AI coding agents, including Claude Code, Codex, OpenCode and Cursor Agent, under a separate local account, sharing only a chosen project directory and enforcing per-session sandbox policies, network rules, and optional backups. On macOS it backs up the project, builds a session-specific sandbox policy, and starts the harness behind a firewall rule; Linux runs natively and an Apple-container backend is experimental. About 5.5% of the code is a TLA+ formal specification of its containment model.

Help Net Security · Aug 17, 2026AI safety & security1

Ask HN: Anyone still coding like 2021? Where do you work?

Hacker News users debate coding without LLMs, with one developer fired for refusing AI tools and others describing daily hand-coding practice to counter skill atrophy.

An Ask HN thread collects experiences of developers who still write code without LLM assistance. One contributor says he was fired for political reasons after refusing to use LLMs despite adequate stated performance, and observes fewer job ads now require LLM use. Others describe starting each day with a LeetCode problem or 30-60 minutes of hand-coding to stay sharp, contractual bans on AI-generated code for a government-adjacent embedded product over unresolved copyright issues, and inconsistent corporate policies where ChatGPT or Codex use flip-flops between allowed and blocked while a CIO mandates 70-80% AI-generated code next year.

Hacker News · AI · 6d agoAI industryHN 47↑ · 54 comments2

Design Docs Are All You Need: An AI-native Machine-Learning Performance Tool

Researchers present SMART, an ML performance-modeling library regenerated by AI coding agents from natural-language design docs instead of code.

The paper describes SMART, a symbolic performance-modeling library whose main branch contains almost no code: the repository is a DAG of self-contained design documents, and coding sub-agents regenerate implementations from only the docs on version updates. Reliability rests on a worked-example doc style used as in-context demonstrations and a minimal operator IR with SymPy cost expressions, offering both fast analytical roll-up and fine-grained modulo-scheduling modes. Regenerated implementations reproduce hand-audited reference models, including DeepSeek-V3 serving on a TPU pod slice, to round-off precision.

arXiv cs.AI / cs.LG / cs.CL · 11d agoAI research1

Staying Ahead of Adversarial AI Through Agentic Source Code Review

Google Threat Intelligence details an agentic AI pipeline with human expert oversight to review source code and outpace AI-enabled attackers.

Google Threat Intelligence researchers argue that adversaries' misuse of AI raises the risk of data theft and extortion when proprietary source code is exposed. They describe a structured agentic source code review pipeline that combines AI models with skeptical validation steps and injected human domain expertise. The team reports a leap in efficacy in finding vulnerabilities before adversaries can exploit them.

Google Threat Intelligence · 28d agoResearch1

When the Whole Company Adopts AI: What It Does to Your SOC

Analysis of 16.9 million SOC alerts finds AI-related alerts at 0.43%, growing 685% since February, with 94.1% noise and 0.02% real attacks.

A review of roughly 16.9 million SOC alerts found about 73,000 (0.43%) were AI-related, a share that grew 685% between February and June 2026. Of AI-related alerts, 94.1% were noise, 5.8% genuine risks, and 0.02% real attacks; 79.8% received benign verdicts, 81.7% were automatically suppressed, and only 5.4% reached a human analyst. The only confirmed attacks were phishing campaigns that weaponized AI brand names as lures, while developer coding agents spawning shells and reading credential stores routinely tripped detections written before AI agents existed.

The Hacker News · 3d agoResearch1

[AINews] Poolside gets $12B reverse-execuhire to NVIDIA; founders stay for $1B, employees go for $6B, Infraco scaling to 7GW neocloud

NVIDIA struck a $12B deal with AI coding startup Poolside, licensing its Model Factory and hiring 109 of its technical employees.

NVIDIA spent roughly $12B in an unusual reverse-execuhire of Poolside, licensing the company's Model Factory while hiring 109 of its ~115 technical staff; founders retain a $1B stake and employees receive about $6B. Poolside had raced to raise $2B to fund a 40,000 GB300 cluster after missing a six-week funding window, and founders argue frontier-scale training now requires an order of magnitude more compute plus contracted data center space. An infrastructure arm spun out in January 2026 is scaling toward 7GW as a neocloud. The newsletter also recaps OpenAI and Anthropic agent-platform releases.

Latent Space · 26d agoAI industry

The /wayfinder Skill: Navigating the “Fog of War” of Planning

Matt Pocock released the /wayfinder skill, an orchestrator layer that manages planning sessions, maps, and tickets for AFK coding agents.

Latent Space interviews Matt Pocock, whose AI Skills for Real Engineers project has 220,000+ GitHub stars, about his new /wayfinder skill. The skill manages agent context during ambiguous planning by splitting work into grilling, prototype, research, and task tickets organized under a shared map, enabling overnight AFK agent runs. It uses deliberate terminology like map, ticket, and session to steer agent behavior, and was tested on projects including a personal website rearchitecture.

Latent Space · 26d agoAI tools & infra

Feeling sad about AI

Simon Willison argues developers disheartened by AI coding agents should move past existential crisis and refocus on broader engineering problems.

In a comment on a Hacker News thread titled 'Feeling sad about AI', Simon Willison reflects on the discouragement engineers feel when AI coding agents complete in an hour work that previously took a week. He notes that translating an exact specification into decent code is no longer a unique skill. He counsels that engineers who accept this shift can apply their experience to the larger set of problems they still face.

Simon Willison · 4d agoAI industry1

HOL Guard: Open-source antivirus for AI agents

HOL Guard is an open-source local guardrail that pauses AI coding agents before risky actions like secret access and prompt injection.

HOL Guard sits between AI coding agents (Claude Code, Cursor, Codex, Gemini CLI and others) and the host machine, intercepting risky commands before execution with checks taking under 50 milliseconds and running fully offline. It offers four sensitivity modes — Gentle, Balanced (default), Strict, and Paranoid — and parses command structure, environment, sensitive-path access and network destinations to decide when to interrupt. The core runtime is free and open source on GitHub, with 552,000 downloads reported; the vendor says it has no telemetry on adoption because collection is off by default.

Help Net Security · 15d agoAI tools & infra1

GPT-5.6 Luna vs. GPT-6 Astra: Is a $1.20 Model Good Enough for Code Review?

Entelligence benchmarks GPT-5.6 Luna ($1.20/M output) against GPT-6 Astra for code review: Luna found 69 verified bugs at 3.6% of Astra's cost.

Entelligence compared GPT-5.6 Luna ($0.20/$1.20 per million tokens) against GPT-6 Astra ($10/$50) on 50 benchmark pull requests from Cal.com, Sentry, Discourse, Keycloak, and Grafana. Astra verified 92 bugs versus Luna's 69, with precision of 96% versus 74%, and Astra caught 19 of 24 security bugs while Luna found only 9. Luna cost $0.20 total versus Astra's $5.66 and reviewed faster at 23 seconds versus 36, with the widest quality gap on Keycloak authentication and permission logic (6 vs 14 verified bugs). Running both models would find 82% of the 143 verified bugs for $5.86 total.

Hacker News · AI · 1d agoAI researchHN 44↑ · 45 comments

AI Customer Service Bots Can Be Tricked Into Stealing Security Codes and Acting as Victims

DEF CON 34 research shows AI customer-service agents can be manipulated via prompt injection and email tricks to leak OTPs and act as victims.

Inti De Ceukelaire, presenting at Bug Bounty Village during DEF CON 34, demonstrated attacks against AI-powered customer service bots with access to customer profiles, billing data, support inboxes, and refund tools. Techniques include transcript-based phishing from trusted support addresses, From-header identity confusion, email normalization abuse to bypass OTP rate limits, and knowledge-base poisoning via RAG crawlers. He recommends separating untrusted content from system prompts, session-bound authentication, consistent email normalization, server-side tool validation, and least-privilege permissions for AI agents.

Cyber Security News · 8d agoAI safety & security

Coding Is Over. Get over It

A JPMorgan Chase engineer reflects on AI agents outpacing hand-coding, questioning ROI while predicting inference costs will become negligible.

A personal essay by a software engineer with 15+ years at JPMorgan Chase describes how AI coding agents now outperform him and have transformed his workflow. He argues AI ROI is unmeasurable, praises cheap small models such as GPT 5.6 Luna, and cites Claude Code head Boris Cherny's advice to discard AGENTS.md/Claude.md rule files. He contends coding is no longer scarce, worries entry-level jobs will be automated first, and predicts AI's bigger impact lies outside coding.

Hacker News · security · 3d agoAI industryHN 20↑ · 26 comments2

The AI Malware Maturity Gap

Recorded Future introduces AIM3, a five-level maturity model for AI malware, showing current attacker AI use is mostly AI-assisted rather than autonomous.

Recorded Future proposes AIM3, a five-level model defining AI malware from LLM-translated to LLM-embedded, spanning experimentation to fully autonomous agentic campaigns. Public examples remain early-stage: PROMPTFLUX uses Google Gemini to rewrite its VBScript dropper (Level 1), while Lamehug/PROMPTSTEAL, attributed to APT28, invokes the HuggingFace API to generate reconnaissance commands (Level 3). The authors argue most current AI malware augments existing tradecraft rather than enabling one-click autonomous attacks.

Recorded Future · 21d agoResearch

One in four MCP servers opens AI agent security to code execution risk

Noma Security whitepaper finds most popular AI Skills and many MCP servers carry high-risk capabilities, with state changes most prevalent.

Noma Security analyzed hundreds of popular MCP servers and Skills across eight risk categories, finding most widely used Skills carry at least one risky characteristic and a typical enterprise runs well over a hundred high-risk agent tools, with arbitrary code execution common across MCP servers. The most prevalent risk is the ability to change state or data, and named toxic combinations include ContextCrush data leakage, ForcedLeak via poisoned Salesforce CRM records, DockerDash supply-chain compromise, the Replit production database deletion, and the hijacked Amazon Q VS Code extension. Building on OWASP LLM06:2025, the paper proposes the No Excessive CAP framework of capabilities, autonomy, and permissions, recommending allowlisting, MCP version pinning, approval gates on irreversible actions, and user-scoped expiring credentials.

Help Net Security · 23d agoAI safety & security

How Developers Prevent Production Risk at the Source

Wiz argues shift-left code-stage security cuts remediation costs and ships Wiz Code, WizOS, and WizCLI to catch flaws pre-deployment.

A Wiz blog post argues that fixing vulnerabilities at the code stage costs a fraction of production remediation, citing the node:20-slim base image which ships 14 known CVEs, three of them critical. It claims AI agents can now analyze open-source commits and generate working exploits in minutes, shrinking the window between a public fix and automated attacks. The post promotes WizOS near-zero-CVE base images, WizCLI and MCP-server checks inside developer and AI agent sessions, and Wiz Code scanning across pull requests, repositories, and pipelines covering SAST, SCA, secrets, and IaC misconfigurations.

Wiz Blog · 13d agoIndustry1