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Re: Retrospective by 'gpg.fail' authors

oss-security follow-up to a gpg.fail authors' retrospective argues that GnuPG's unmaintained, forgotten code is a security liability and should be deleted.

On the oss-security mailing list, Soatok Dreamseeker responds to a retrospective published by the gpg.fail authors, asking why unmaintained code is retained and stating that forgotten, unmaintained code is a liability and effectively unmaintained by definition. The visible reply addresses Werner Koch and concerns GnuPG code maintenance. No specific CVE, flaw, or exploitation is described in this snippet.

CVE-2026-86089: Apache NiFi: Missing Process Group Authorization for Connector Migration

Apache NiFi 2.11.0 Connector Migration REST APIs authorize only against the target Connector, skipping Process Group access checks (CVE-2026-86089, Low).

Apache NiFi 2.11.0 supports migrating version-controlled Process Group contents into a Connector via REST API methods that list eligible migration sources and submit migration requests. Both methods were authorized only against the target Connector, without evaluating user access to the involved Process Groups. The flaw, tracked as CVE-2026-86089, is rated Low severity and affects the nifi-web-api component.

Version Control DFIR: a Cheatsheet to GitHub, GitLab, Bitbucket, and Azure DevOps

Wiz published a DFIR cheatsheet covering log visibility, incident readiness, and threat hunting across GitHub, GitLab, Bitbucket, and Azure DevOps.

Wiz researchers released a practitioner's guide to version control system forensics, incident response, and threat hunting. The cheatsheet maps log sources, audit capabilities, and hunting workflows across GitHub, GitLab, Bitbucket, and Azure DevOps. It aims to improve incident readiness for source code and CI/CD compromise scenarios.

Wiz Blog · 20d agoResearch1

Why 2026 is the Year to Upgrade to an Agentic AI SOC

Elastic Security Labs argues 2026 is the production inflection point for agentic AI in security operations centers.

Elastic Security Labs argues 2026 is the practical inflection point for agentic AI SOCs, noting nearly two-thirds of organizations are experimenting with AI agents while fewer than one in four have production deployments. The piece outlines operational challenges and recommendations: treat agents as non-human identities with least-privilege tool access, version-control system prompts as code, deploy unified agents with on-demand task packages, and enforce per-agent budgets and rate limits. It stresses explainability via RAG and transparent reasoning traces so analysts can verify and override autonomous decisions.

Elastic Security Labs · 7d agoIndustry

When Models Edit Too Much: On the Fidelity of Minimal Code Edits

A 400-task BigCodeBench evaluation shows frontier LLMs widely over-edit code; a preservation instruction cuts excess edits and raises Pass@1 by 2.3 points.

Researchers built an evaluation framework from 400 BigCodeBench problems with injected AST-level corruptions, each with a known minimal patch, to measure over-editing in LLM code repair. Even strong models like GPT-5.5 produce unnecessarily large edits despite high Pass@1. Adding a preservation instruction reduced average excess Levenshtein distance from 0.195 to 0.131, cut added cognitive complexity by 26.6%, and raised Pass@1 by 2.3 points. Reinforcement learning post-training gave the best out-of-domain edit-fidelity trade-off, while supervised fine-tuning overfit to seen corruption patterns.

Hugging Face daily papers · 14d agoAI research1

ExecCritic: Learn to Test, Test to Improve for Coding Agents

ExecCritic separates test generation from patching for coding agents, lifting SWE-bench Verified resolution to 72.6%.

ExecCritic pairs a test-verify-revise scaffold with role-specific reinforcement learning: a Test agent writes repository-native tests and a Repair agent fixes code from execution feedback, both using Qwen-3.5-35B-A3B backbones. Post-trained Qwen agents compose to 72.6% on SWE-bench Verified, an 11.4-point gain over the 61.2% no-test baseline, without stronger-model or oracle feedback at evaluation time. The work shows test quality is the key variable: base-agent tests lowered resolution to 57.3% while GPT-5.6-sol tests raised it to 65.3%.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research1

Does Your Agent's Memory Survive a Model Upgrade? A Controlled Study of Memory Portability

A controlled study finds agent memory portability varies sharply: fixed-schema knowledge graphs survive model swaps while compressed notes degrade.

The study compares preserving an agent's history as raw long context, RAG chunks, compressed natural-language notes, or fixed-schema knowledge graphs across model upgrades, using 48 synthetic histories and two open-weight sub-10B-parameter models. Fixed-schema KG accuracy changed by only +0.0004 ± 0.0020 after a writer swap, while compressed NOTES shifted asymmetrically by +9.91 or -13.28 percentage points depending on migration direction. Mixed 50/50 embedding migrations captured only 4.96 of an 11.90-point RAG re-embedding gain; 80% of the NOTES deficit came from information lost at construction, and 81% of the RAG deficit from retrieval failures. Store-only repair of NOTES failed to reach 90% recovery in all 48 cases, while retaining raw histories enabled recovery in 34 of 48 for one direction.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research1

get the module working against several of the 12.4.3 versions

A Metasploit Framework exploit module was updated to work reliably against several 12.4.3 software versions.

A commit to the Rapid7 Metasploit Framework repository adjusts an existing exploit module so it functions against several 12.4.3 version targets. The change is described as getting the module working against those versions, indicating reliability or compatibility improvements. The commit text does not describe a new vulnerability, exploitation campaign, or affected victims.

Metasploit Framework commits · 7d agoTools1

Diffs vs. Whole Files: An Empirical Comparison of Iterative Edit-Based and Direct Generation for Flutter/Dart Code Models

Empirical study finds direct whole-file generation beats iterative diff-based editing for Flutter/Dart code models on about 1,790 held-out tasks.

Researchers trained Rainbow-Pony-100M from scratch and fine-tuned Qwen2.5-Coder-0.5B in both direct-generation and diff-based regimes, then evaluated four resulting models on roughly 1,790 Flutter/Dart tasks. Direct generation outperformed diff-based generation on compilation pass rate, bits-per-byte, character-level similarity, and blinded LLM-judge ratings. Diff-based editing is competitive only on short, localized edits in refactoring and error-handling tasks, a property the authors call task locality.

Hugging Face daily papers · 12d agoAI research1

CONTINUITY: Security-Context Contracts for Composable LLM Agent Controls

Researchers introduce CONTINUITY, a framework of assume-guarantee contracts that preserves LLM agent security context across components, verified across 2,560 attack instances.

The paper identifies security-context discontinuity, where individually sound controls drop, widen, or reinterpret security context as actions cross component boundaries, and proposes CONTINUITY, a framework of assume-guarantee contracts using signed root grants, provenance commitments, role-bound transition receipts, and effect-bound execution permits. It formalizes end-to-end consequence integrity, requiring every external effect to be backed by a valid authorization witness linking principal, task, provenance, and policy state. A reference verifier and cross-layer fault-injection suite covering 32 fault classes showed the full configuration committed no harmful external effect across 2,560 parameterized attack instances while completing all 700 benign tasks and escalating all 200 ambiguous cases.

arXiv cs.CR · 12d agoAI safety & security

What Else Needs Fixing? Exploring Cost-Effective Test-Time Compute for Revision Propagation in Artifacts Generated Through Conversation

A new benchmark shows LLMs reach 68.3-93% accuracy propagating local revisions across conversationally generated artifacts, with parallel-sample selection most cost-effective.

The paper introduces a benchmark for revision propagation: when users request a local change, LLMs must identify dependencies and update all affected parts of an artifact generated through conversation, where context lives in the chat history. Nine revision methods, including sequential reflection and parallel sampling variants, were evaluated on gpt-oss-20b/120b, gpt-5.4-mini, and qwen3.5-9b/27b/122b. Baselines scored 68.3-93% accuracy, and selecting among three parallel samples via LLM-based or medoid selection improved accuracy by 2.2-9.7% as the most cost-effective test-time compute strategy. Code and dataset are released.

Hugging Face daily papers · 14d agoAI research

"They don't care about this": A Systematic Study of TEE Build Reproducibility in the Wild

91% of 115 surveyed TEE deployments across Intel SGX, TDX, and AMD SEV fail to provide reproducible builds needed for verifiable remote attestation.

A systematic study of 115 TEE deployments found 91% were not reproducible and 80% lacked both source code and a reference build, undermining remote attestation guarantees. Interviews with 12 developers of 50 Intel SGX projects confirmed that only one participant treats reproducibility as a development priority. The authors identify technical barriers such as embedded timestamps plus ecosystem-level issues like lack of build-environment control in multi-stakeholder projects, and call for holistic, committed reproducibility practices.

arXiv cs.CR · 6d agoResearch

Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent Failures

Continual Search framework iteratively prompts LLM judges to keep searching agent execution logs, boosting long-horizon failure root-cause attribution accuracy.

The paper frames automated root-cause attribution (RCA) for long-horizon AI agent failures as a search problem, since relevant evidence is sparse and distributed across massive execution traces. The authors propose Continual Search, an iterative framework that nudges an LLM judge across successive turns to keep hunting unresolved diagnostic evidence instead of settling on an early plausible diagnosis. They introduce MegaRCA-Mix, a benchmark of 50 human-annotated failure trials on long-horizon, execution-heavy tasks. On MegaRCA-Mix, Continual Search improves GPT-5.5's F1 from 0.349 to 0.498 (over 40% gain), and lower-tier models can surpass higher-tier counterparts when search is effective.

Hugging Face daily papers · 6d agoAI research1

When LLM Decompilers Recompile More and Preserve Less

Researchers show LLM decompiler outputs can recompile yet diverge behaviorally, proposing the Decompile-Diverge fuzzing oracle to catch hidden changes.

The paper demonstrates that LLM-based decompilers can produce code that recompiles and passes all shipped tests yet diverges on other legitimate inputs—4.9% overall and up to 13% for one system—and can make disclosed vulnerabilities vanish without a visible crash. Across 300 real GitHub functions and 287 CVE-grounded functions, a refinement LLM lifted Ghidra's build rate from 75% to 90% while Matched rate fell from 74% to 62%, with up to one tenth of vulnerabilities showing Crash Absence. Decompile-Diverge detects these gaps by synthesizing drivers, growing fuzzing corpora from the reference, and rerunning decompiled code on identical inputs.

arXiv cs.CR · 12d agoResearch

pcre2 version 10.48 released with security fixes

PCRE2 10.48 released with security fixes; none have CVE IDs assigned yet, details limited to release notes.

The PCRE2 project released version 10.48 including security fixes, announced on the oss-security mailing list. As of publication, none of the fixes had CVE identifiers assigned, and specifics are only available via the project's release notes and security advisories page.

oss-security · 11d agoVulnerability

Package Manager Trends

Sixteen-week roundup finds package managers converging on release-age cooldowns, install-script blocking, malware scans, and recurring path-traversal and credential-leak fixes.

The author aggregates supply-chain security trends from sixteen weeks of This Week in Package Management, built from about 80 RSS feeds. Release-age cooldown gates shipped in Deno 2.8, Bundler, npm, Yarn, mise, Hex, Mamba, and Cargo, with Dependabot making a three-day cooldown default in August. npm 12 and Bun 1.4 now block lifecycle install scripts by default, and Composer 2.10 and uv added install/publish-time malware checks, while npm's registry began scanning at publish time. Path traversal on archive extraction was fixed in 14 of 16 weeks across tools including uv, pnpm, Docker, and Composer, and credential-misdirection bugs affected Cargo, ORAS, Composer, and Renovate.

Lobsters · security · 6d agoResearch1

libpcap 1.10.7 fixes 7 vulnerabilities

libpcap 1.10.7 fixes seven vulnerabilities, including CVE-2026-31912 affecting the deprecated bpf_filter(), and all users are advised to update.

libpcap 1.10.7 was published on 2026-09-05 with its main focus being fixes for seven vulnerabilities. Maintainer Denis Ovsienko announced the release on the oss-security mailing list, noting that each CVE record contains detailed accounts and links to git commits with further explanation. For the CVE-2026-31912 fix to take effect, applications using the now deprecated bpf_filter() must update their usage. All users are advised to update; no exploitation in the wild is reported.

oss-security · 7d agoVulnerabilityCVE-2026-319121

llm 0.34

Version 0.34 of Simon Willison's llm CLI adds response-duration metrics to log output, plus bug fixes and faster log querying.

The open-source llm command-line tool for interacting with large language models released version 0.34. The headline change adds response duration in milliseconds and human-readable form to llm logs --usage Markdown output, plus a new duration_ms field in llm logs --short. The release includes several contributed bug fixes and a significant performance improvement to llm logs, alongside the related llm-openrouter 0.7.1 release.

Simon Willison · 14d agoAI tools & infra1

The History Is the Detector: Executing CVE Patch History, End-to-End

BUGSTONE-E2E converts CVE patch history into executable LLM-guided detection rules, yielding 1,033 rules and 644 runtime-verified findings across 14 programs.

The BUGSTONE-E2E framework mines reusable detection rules from verified fixing commits, organized by CWE and language, and applies them through a funnel pipeline that escalates from Tree-sitter anchors and lightweight heuristics to LLM-based agent inspection, runtime verification, and scope-checked patch generation. Built from 19,325 high-severity CVEs published 2022-2026, it produced 1,033 detection rules spanning 56 CWE families, packaged into 172 skills. Applied across 14 programs, it generated runtime evidence for 644 findings, demonstrating that vulnerability history can drive reproducible detection and repair.

arXiv cs.CR · 12d agoResearch

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

Re: Vulnerability fixes in util-linux-2.42.3

util-linux 2.42.3 includes vulnerability fixes, with a commit link shared for downstream tracking but no CVEs cited.

An oss-security post links a util-linux commit (286dd3ff41526b582ef48830de239dffbaa61f90) as part of the 2.42.3 vulnerability fix release. No CVE identifiers, flaw descriptions, or exploitation details are provided. The item is a routine open-source fix notification for downstream distributors.

oss-security · 11d agoVulnerability1

PrivEscalate: Measuring and Augmenting the Threat of LLM-Automated Linux Privilege Escalation

Researchers release PrivEscalate, a 531-scenario benchmark showing LLM agents' Linux privilege-escalation success varies by vulnerability class, plus PrivEscAgent, a domain-specialized agent that boosts success.

The paper introduces PrivEscalate, an open-source benchmark of 531 Dockerized Linux privilege-escalation scenarios spanning 14 sub-categories, plus 329 parameterized variants measuring sensitivity to environmental distractors. Evaluating six LLMs across three agent architectures shows capability is heterogeneous across vulnerability classes, sensitive to perturbation, and architecture-dependent. The authors also present PrivEscAgent, a wrapper adding deterministic enumeration, category matching, and step planning that outperforms prior privesc-agent baselines without modifying the underlying LLM. The benchmark is released to support LLM agent evaluation, defensive tool validation, and red-team training.

arXiv cs.CR · 8d agoResearch

Datasette 1.0a39 and 0.65.4 security releases

Datasette shipped security patches 1.0a39 and 0.65.4 fixing subtle bugs in instances mixing public and private tables, found via an AI-assisted audit.

Datasette released parallel security fixes for its current alpha series (1.0a39) and stable 0.65.x family (0.65.4), advising anyone running a Datasette instance on the public web to update, especially where public and private tables are mixed. The underlying issues were reported by Sevban Dönmez and Alex Garcia, followed by an extensive audit of the codebase using Claude Fable 5.1, GPT-5.6, and GPT-6 Astra. Fixes were developed and reviewed collaboratively over nearly a week. No CVE identifiers or observed exploitation are mentioned in the announcement.

Simon Willison · 5d agoVulnerability 3 sources2

No Bit Left Behind: Using Brute-Force Lifting to Achieve Fully Static Binary Recompilation

Prototype binary lifter brute-force lifts every byte offset of x86-64 binaries to LLVM IR, enabling fully static cross-ISA recompilation without runtime support.

The paper presents a fully static, whole-program binary lifting system that treats every byte offset as a potential branch target, constructing a superset control flow graph that conservatively contains all feasible control flows. Statically unresolvable computed branches are reduced to lookups in a dispatch table pointing to translated control flow paths, eliminating runtime translation machinery on the target machine. A prototype recompiles x86-64 binaries to LLVM IR with no code/data heuristics and achieves fully static cross-compilation to AArch64 using unmodified LLVM backends.

arXiv cs.CR · 1d agoResearch

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

Forgetting Without Restarting: Execution-State Unlearning for Stateful LLM Agents

Researchers propose provenance-guided selective replay letting LLM agents forget revoked information without restarts, matching full reset behavior.

The paper formalizes execution-state unlearning for stateful LLM agents, requiring that agents behave as if a revoked memory record was never observed across transcripts, compressed memory, tool plans, and KV caches. It proves exact unlearning requires at least T-τ+1 recomputed transitions and that Provenance-Guided Selective Replay attains this bound via a provenance graph, KV cache cropping, and sanitized replay. In audits across three agent suites, nine baselines, and three model families, memory deletion left leakage unchanged, instruction-based forgetting collapsed under elicitation (Leak@probes = 1.00), and selective replay matched full resets at up to 9x fewer recomputed tokens.

arXiv cs.CR · 12d agoAI safety & security1