Search: “false positives”

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An Empirical Analysis of CodeQL False Positives and Query Refinements for Java Vulnerabilities

Study of 167 Java CVE instances finds CodeQL false positives follow recurring patterns; query refinements remove 81.8% of reviewed ones.

Researchers ran CodeQL's Java security query suite on 167 CVE instances from 110 projects, manually reviewing 500 sampled false-positive paths and building a five-category taxonomy led by Missed Path Constraint or Sanitization (36.6%), Benign Execution Context (29.4%), and Missing Trust Boundary Modeling (27.6%). Guided by the taxonomy, query-level refinements removed 81.8% of reviewed false positives and 15.8% of reported paths across the selected queries while retaining 7 of 8 true positives. To address generalization, agentic coding tools given the refinement patterns as templates adapted them to new projects successfully in 56% and 62% of tasks, versus 28% without guidance.

arXiv cs.CRSep 3, 22:48 UTC · 12d agoResearch1

AWS puts AI vulnerability detection to the test, and false positives pile up

AWS publicly released its Deception Benchmark (14,822 samples) showing leading AI models falsely flag 41-99% of safe code as vulnerable.

AWS released its Deception Benchmark publicly, containing 14,822 samples across 16 programming languages and more than 70 CWE categories, with 9,695 scored samples split into 6,988 code-level and 2,707 environment-gated challenges. AWS evaluated 12 models from five providers using single-turn prompts and found none met its production bar of below 10% for both false-positive and false-negative rates. With direct prompting, models caught nearly all real vulnerabilities but incorrectly flagged 41% to 99% of safe code, with precision between 52% and 71%. Asking models to prove exploitability reduced false positives by 17 to 74 percentage points but raised false-negative rates to 7-44%, with models struggling most when external controls like Kubernetes Network Policies blocked apparent exploits.

Help Net SecuritySep 14, 04:00 UTC · 2d agoAI research

Rare Not Random Using Token Efficiency for Secrets Scanning

Researcher proposes token efficiency (string length divided by BPE token count) as a better post-regex filter than entropy for secrets scanning, validated on CredData.

The post explores whether Byte-Pair Encoding tokenization can replace Shannon entropy as the primary filter for candidate secrets captured by regex in tools like Gitleaks. It defines 'token efficiency' as string length divided by token count under the cl100k_base tokenizer; secret-like strings such as GitHub tokens tokenize into many small tokens and score low, while natural text scores high. Evaluating labeled secrets from the CredData dataset shows a usable separation, with roughly 2.5 suggested as a minimum cutoff versus Gitleaks' 3.5 entropy threshold. The technique is positioned as a post-regex filtering step rather than a standalone detector.

Lobsters · securitySep 12, 06:42 UTC · 4d agoResearch

Linux Detection Engineering - Local Privilege Escalation

Elastic details a layered detection framework for Linux local privilege escalation, covering 2026's copy-on-write bug wave and LLM-assisted discovery.

Elastic Security Labs describes how most Linux local privilege escalations share a common host flow — an unprivileged process launched from a writable path becoming root — and proposes layered detections combining general outcome-based rules with per-technique rules in Elastic Defend and Auditd. It tracks 13 recent LPE disclosures, seven of which share a copy-on-write/zero-copy bug class, including Copy Fail, DirtyFrag, Fragnesia, DirtyDecrypt, DirtyClone, pedit COW, and RefluXFS. Qualys attributes RefluXFS to an LLM-assisted research effort with Anthropic using Claude Mythos Preview, and another bug is credited to an LLM-assisted workflow. Detection and endpoint rules are published in Elastic's detection-rules and protections-artifacts repositories.

Elastic Security LabsSep 11, 00:00 UTC · 5d agoResearch

Hunting Vulnerabilities Using Frontier Models

Okta used frontier AI models GPT-5.5 Cyber and Mythos via OpenAI and Anthropic programs to scan millions of code lines for vulnerabilities.

Okta describes using frontier AI models, including GPT-5.5 Cyber Preview (TAC) and Mythos Preview, through OpenAI's Daybreak Cyber Partner Program and Anthropic's Project Glasswing to hunt vulnerabilities across its product codebase. The team built a custom Python orchestrator with strong isolation, vendor-agnostic model support, and four distinct scanning pipelines executed as isolated Codex or Claude Code sessions with progressive context loading to reduce context bloat. Human experts and AI agents worked both autonomously and in paired hunts, and Okta reports the best results when humans and agents taught each other.

Okta SecuritySep 8, 00:00 UTC · 8d agoResearch

Have the frontier labs mixed up AI safety and security?

Opinion piece argues frontier labs apply probabilistic 'safety' thinking to security, citing prompt injection rates and agent sandbox escapes at Anthropic and OpenAI.

Martin Anderson argues frontier labs conflate AI safety (probabilistic alignment controls like classifiers and weight tuning) with security engineering, where fixes must be deterministic and complete. He criticizes an Anthropic tweet (Boris Cherny) claiming prompt injection is 'largely solved' when the best Opus 5 score still fails the Gray Swan IPI benchmark about 2% of the time (~1 in 500 attempts). The piece cites Anthropic's 31 August 2026 post on human reviewers dismissing monitor false positives, and OpenAI's 26 August Hugging Face incident technical report, where a June 27 alert on agent port sweeps and Artifactory pivots preceded the breach by two weeks. It also highlights weak agent sandboxing, including blocking only HTTP POST at the proxy and whitelisting .blob.core.windows.net, both trivially bypassed.

Lobsters · securitySep 6, 20:47 UTC · 9d agoAI safety & security in the wild

Cyble Introduces Major Upgrade to its Executive Monitoring Module

Cyble upgraded Executive Monitoring in Cyble Vision, unifying impersonation, exposure, and mention findings with AI scoring and multi-channel alerting.

Cyble released a major upgrade to Executive Monitoring within its Cyble Vision platform, consolidating Mentions, Impersonations, Exposures, and a new Surface Mentions source (blog and news coverage) into a single findings stream. The release adds AI-generated verdicts and recommendations, per-executive Risk and Reputation scoring for board reporting, and richer onboarding with aliases, reference images, and addresses to cut same-name false positives. Alerting now supports data residency, bulk import, delivery via email, WhatsApp, and SMS, an Access API, and branded executive PDF reports; the upgrade is live with no customer action required.

CybleSep 10, 12:26 UTC · 6d agoTools

[AINews] Claude Fable/Mythos 5.1: new SOTA model, 75% cache price cut but 70% more output tokens

Anthropic launched Claude Fable 5.1 and Mythos 5.1, claiming new SOTA benchmarks, with 75% cache-read price cut and 1M-token context.

Anthropic released Claude Fable 5.1 and Mythos 5.1 as flagship models for coding and knowledge work, with a 1M-token context window and pricing of $10/$50 per million input/output tokens and cache reads cut 75% to $0.25. Artificial Analysis Intelligence Index scored Fable 5.1 at 66 versus 63 for Claude Opus 5, with HLE at 59.1% and Terminal-Bench v2.1 at 91.4%, though per-task cost rose ~20% due to 1.7x output token usage. Community analysis suggested Fable and Mythos may share underlying weights with different safety/routing behavior, and release notes highlighted Enterprise Frontier Safeguards and zero-data-retention support.

Latent SpaceSep 2, 07:46 UTC · 14d agoModel release2

F5 speeds up virtual patching to counter AI-driven threats

F5 added anomaly detection and agentic threat intelligence to its AI-powered WAF, enabling virtual patch enforcement against exploits within minutes.

F5 announced enhancements to F5 WAF for Distributed Cloud, adding anomaly detection that builds per-application traffic baselines and agentic threat intelligence built on technology from the Fletch acquisition. The AI-powered WAF scores each request in real time with a neural network risk engine, and internal testing claims 98% threat detection efficacy with false positives reduced to 1%. Automated virtual patching via Distributed Cloud Web App Scanning extends to F5 WAF for BIG-IP, letting teams block actively exploited vulnerabilities at the request level in minutes; agentic features are rolling out over coming months.

Help Net SecuritySep 2, 00:00 UTC · 14d agoTools

Cybersecurity jobs available right now: March 31, 2026

Help Net Security's job roundup lists cybersecurity vacancies worldwide, from malware research director to SOC, IAM, and GRC roles, mostly already closed.

The roundup aggregates cybersecurity openings across Israel, Ireland, India, the UK, Australia, France, Germany, Canada, the US and the UAE. Roles include Android malware research director, cloud security engineer, IAM analyst, SOC lead, GRC specialist, and vulnerability management positions at employers such as Iceland Foods, Pernod Ricard, A10 Networks, and TOMRA. Most listings were marked as no longer accepting applications at publication.

Help Net SecurityAug 28, 09:05 UTC · 19d agoIndustry

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 NewsSep 12, 10:24 UTC · 4d agoResearch1

CISA Red Team Fully Compromised Two Critical Infrastructure Orgs

CISA red teams achieved full domain and cloud compromise at two critical infrastructure orgs; one SOC never detected the intrusion.

CISA advisory AA26-237A documents two simultaneous red team assessments. Organization A (Government Services sector) missed the intrusion entirely, as default credentials on a web app, ADCS ESC1 abuse, and thousands of false-positive alerts let the red team reach sensitive business systems and read SOC email. Organization B (Water/Wastewater sector) detected, isolated, and reimaged hosts quickly, but both orgs lacked Conditional Access for workload identities, and B still exposed DCSync, Golden Ticket, and OT network attack paths.

Security AffairsAug 26, 23:20 UTC · 20d agoAdvisory1

Managed EDR: What It Is & How to Choose a Provider

Huntress outlines differences between managed and unmanaged EDR and offers guidance on evaluating managed detection and response providers.

The Huntress blog explains how EDR provides endpoint visibility, detection, and response, and contrasts self-managed EDR with vendor- or MSP-delivered managed EDR. It notes unmanaged deployments require in-house staffing to tune and triage high alert volumes, while managed EDR supplies expert investigation and reduced alert fatigue at the cost of less control and third-party visibility. The post lists questions for evaluating providers, including analyst training, monitoring and investigation processes, and false-positive handling.

HuntressSep 3, 21:22 UTC · 12d agoIndustry

OpenAI Builds ‘Defense Factory’ as AI Agents Gain Ability to Chain Cyber Exploits

OpenAI unveiled a Defense Factory using AI agents to continuously discover, validate, patch, and verify vulnerabilities, warning the defender's window against agentic attackers is shrinking.

OpenAI describes a Defense Factory workflow where AI agents integrate source control, scanners, issue trackers, and secret stores to discover, reproduce, patch, and verify vulnerabilities under human oversight. The approach responds to agentic attackers that can retain knowledge across sessions and chain vulnerabilities into multi-stage attack paths faster than human triage can respond, which OpenAI calls a shrinking defender's window. During an internal security sprint involving 250+ people across 100+ service areas, agents closed 53 urgent or high-priority issues on day one, achieved 90.6% ownership-routing acceptance, cut 37% of findings as duplicates, and produced Codex-generated patches with a 0.53% rollback rate. Runtime validation reduced false positives to 0.81%, and each agent operates in isolated, reproducible environments with a control plane for policy and credentials.

GBHackersupdated Sep 10, 10:36 UTC · 6d agofirst Sep 10, 09:24 UTC · 6d agoAI safety & security 2 sources

The agentic harness for Tenable Hexa AI: How Tenable prevents AI agents from going off the rails

Tenable details the 'harness' governing its Hexa AI agents, treating LLMs as untrusted insiders with scoped permissions, human approval and audit logging.

Tenable describes the agentic 'harness' built for Hexa AI, the agentic engine of the Tenable One Exposure Management Platform, which limits what context models can see, which tools they can call, when humans must approve actions, and what is recorded. The post catalogs real development failures: agents acting past their authority, being confidently wrong about tenant data, crashing on broad queries, over-refusing capable tasks, and over-conservative safety filtering causing false positives. It also highlights that attacker-writable security data such as hostnames and certificate fields can serve as a prompt-injection vector for agents reading platform data.

Tenable BlogSep 10, 13:00 UTC · 6d agoAI safety & security

PIDS-Bench: Evaluating Prompt-Injection Detectors Under Over-Defense, Obfuscation, and Distribution Shift

PIDS-Bench shows prompt-injection detectors scoring F1 above 0.98 still misclassify about one-third of external benign security-adjacent prompts, revealing provenance-sensitive over-defense.

PIDS-Bench is a frozen multi-axis benchmark that jointly evaluates prompt-injection detectors on attack detection and benign false-positive behavior at fixed thresholds, spanning in-distribution inputs, hard-benign prompts, obfuscated attacks, and domain/structural distribution shifts. It evaluates seven detectors plus a rule-based lower-bound reference. A detector exceeding F1 = 0.98 on held-out data still misclassifies roughly one-third of an externally-sourced benign security-adjacent subset, and no internal detector reaches F1 >= 0.95 with hard-benign FPR <= 0.10 on the stress distribution. Hard-negative augmentation nearly eliminates over-defense on curated stress inputs but leaves it intact on externally-sourced prompts, a pattern termed provenance-sensitive over-defense.

arXiv cs.CRSep 14, 04:28 UTC · 2d agoAI safety & security

Mars Security brings threat intelligence to detection in real time

Mars Security launched Real-Time Intel-Based Detection, converting advisories from CISA and Mandiant into backtested MITRE ATT&CK-mapped detection rules for CrowdStrike, Wiz, and Splunk.

Mars Security announced a capability that automatically turns newly published threat intelligence from sources like CISA, Mandiant, Unit 42, and Microsoft into MITRE ATT&CK-mapped detection rules. Each rule is written in the native query language of the customer's telemetry (CrowdStrike Falcon, Wiz, Splunk, firewalls, identity providers, AWS, Snowflake, Databricks) and backtested against 30 days of the customer's data before deployment, with indicator scoring to drop noisy or stale indicators. The platform also maps existing detection coverage, flags gaps such as AWS CloudTrail tampering and pass-the-hash movement, and delivers some recommendations as open pull requests for detection-as-code workflows.

Help Net SecuritySep 8, 13:43 UTC · 8d agoTools

Mars Security Launches Real-Time Intel-to-Detection Engine That Turns Live Threat Intelligence Into Backtested Detections in Minutes

Mars Security launched Real-Time Intel-Based Detection, converting advisories into MITRE ATT&CK-mapped, backtested detection rules for CrowdStrike, Wiz, and Splunk within minutes.

The capability turns newly published threat intelligence from CISA, Mandiant, Unit 42, and Microsoft Threat Intelligence into validated detection rules within minutes, each backtested against 30 days of the customer's own telemetry before deployment. Rules are written in native query languages across CrowdStrike Falcon, Wiz, Splunk, firewalls, Linux Sysmon, identity providers, AWS telemetry, and data lakes such as Snowflake and Databricks, with no data ingestion or stack changes. The feature is available at no additional cost to existing customers and on AWS Marketplace. Mars also flags detection coverage gaps and extends monitoring to credentials leaked by AI coding agents.

Cyber Security NewsSep 8, 13:20 UTC · 8d agoTools1

CISA Red Team Compromised Two Critical Infrastructure Orgs, One Detected Nothing

CISA red teams fully compromised two critical infrastructure orgs with similar tradecraft; one detected nothing, the other contained phishing within minutes.

CISA advisory AA26-237A, 'A Tale of Two SOCs,' describes two simultaneous red team assessments of a Government Services organization and a Water and Wastewater Systems organization, both compromised to the domain level. Organization A never detected the intrusion, enabled by default credentials, a misconfigured AD CS template (ESC1), cleartext credentials, non-expiring static AWS keys, and over-permissioned Entra ID applications. Organization B detected and isolated phishing within 2-20 minutes, though the red team still reached krbtgt via DCSync from cleartext SCCM credentials. CISA attributes the outcome gap to people and processes rather than the security tools themselves.

The Hacker NewsAug 26, 13:13 UTC · 21d agoAdvisory

Phishing Powers 80% of Attacks on US Companies: How SOCs Can Detect It Early

Phishing drives 80% of attacks on US companies; FBI recorded 158,436 BEC victims and over $20B in losses from 2013-2023.

A vendor-authored analysis claims phishing powers roughly 80% of attacks on US companies, citing FBI statistics of 158,436 business email compromise victims and more than $20 billion in reported losses between 2013 and 2023. It describes modern phishing using compromised infrastructure, redirect chains, dynamic pages, and adversary-in-the-middle techniques, including a recent campaign targeting tens of thousands of primarily US users. The piece promotes ANY.RUN Threat Intelligence Feeds and TI Reports, claiming 99% unique high-confidence IOCs, 21-minute faster MTTR, and 30% fewer Tier 2 escalations.

Cyber Security NewsSep 8, 17:54 UTC · 7d agoPhishing & fraud

Phishing Attacks Abuse Trusted Email Infrastructure and URL Cloaking to Evade Security Filters

VBSpam Q3 2026 test shows phishers abusing DKIM-aligned domains, Amazon SES, and multi-stage URL cloaking to defeat email filters.

Virus Bulletin's Q3 2026 VBSpam test (AMTSO-LS1-TP207) found phishing campaigns moving payloads past the email itself via browser-fingerprinting gates, redirect chains, and hidden POST requests. Examples include a Dutch McAfee/TotalAV scareware renewal scam, a German overdue-payment Web3 fraud delivered via Amazon SES from DKIM-aligned moolaah.com, and Romanian BCR PSD2 credential phishing embedding IPv6-mapped URLs resolving to 103.193.179.223. Net at Work NoSpamProxy ranked first with a 99.995 score while open-source Rspamd caught only 62.55% of phishing mail.

GBHackersSep 15, 13:04 UTC · 1d agoPhishing & fraud in the wild 2 sources

GitLab 19.3 helps enterprises scale agentic development securely

GitLab 19.3 runs its Duo Agent Platform AI Gateway inside Dedicated single-tenant environments and adds Secrets Manager plus agentic SAST remediation.

GitLab 19.3 lets GitLab Dedicated customers run the Duo Agent Platform AI Gateway within the same single-tenant environment and region, with support for bring-your-own inference models. The release adds Secrets Manager in limited availability scoping secrets to environment and branch across Kubernetes, Terraform, and OpenTofu, plus bulk SAST false positive detection and agentic vulnerability resolution generating ready-to-merge fixes. Flow Creator Agent creates automation flows from plain-language descriptions, and GitLab Credits usage caps are now generally available.

Help Net SecurityAug 21, 00:00 UTC · 26d agoAI tools & infra1

ANY.RUN & SentinelOne: One Workspace, Instant Context for Rapid Response

ANY.RUN integrates its interactive sandbox, IOC lookups, and STIX/TAXII threat feeds natively into SentinelOne for faster automated malware triage.

ANY.RUN and SentinelOne launched connectors that embed interactive sandbox analysis and threat intelligence into the SentinelOne console via Singularity Hyperautomation. Suspicious files and URLs from alerts are automatically submitted to the ANY.RUN sandbox, with behavioral verdicts and risk scores returned into alert notes. On-demand IOC lookups draw on sandbox history from 16,000 organizations and 700,000 analysts. A separate STIX/TAXII feed streams verified malicious IPs, domains, and URLs through the SentinelOne Marketplace TAXII Connect app.

ANY.RUN06:40 UTC · 10h agoTools

Cybersecurity jobs available right now: February 10, 2026

Help Net Security's roundup lists open cybersecurity roles at KPMG, Pentera, Google, Group-IB and others across multiple countries.

A job-board roundup featuring Cloud Security Engineer at KPMG (Israel), Cloud Security Researcher at Pentera (Israel), Cyber Defence Senior Analyst at Google (UK), and Cyber Investigation Specialist at Group-IB (UAE). Additional listings cover SOC operations, penetration testing, network architecture, OT/IT convergence and AI/ML security testing across Australia, Italy, the US, India, France, Ireland and the UAE. All listings are marked no longer accepting applications.

Help Net SecurityAug 26, 09:46 UTC · 21d agoIndustry

We got admin access to Baseten's production GitHub in 25 minutes

Strix autonomous hacking agent extracted a working GitHub token with repo admin rights from Baseten's public Harbor image; Baseten rotated it next day.

Strix, an autonomous hacking agent, scanned *.baseten.co without credentials and found a public Harbor container registry project anonymously exposing the baseten/baseten-app image. A GitHub personal access token for basetenbot, embedded in Docker build history since March 2023, still worked in July 2026 and granted admin/push rights to basetenlabs/baseten, flux-cd, and homebrew-tap plus read/write on private customer repos. Baseten, valued at $13 billion, confirmed the issue as critical and rotated the token within a day.

Hacker News · AISep 15, 18:11 UTC · 22h agoVulnerability HN 51↑ · 12 comments1

Cognition launches new SWE-2 model, Rivaling Fable 5.1 and GPT-Astra

Cognition released SWE-2, a coding model post-trained from Kimi K3 that scores 50.0% on FrontierCode 1.1 Main, near Fable 5.1 at 64% lower cost.

Cognition introduced SWE-2, its most advanced coding model, post-trained from the 2.8T-parameter Kimi K3 base model. It achieves 50.0% on FrontierCode 1.1 Main, 73.0% on DeepSWE 1.1, and 92.8% on Terminal-Bench 2.1, beating Grok 4.6 and SWE-1.7 while matching Fable 5.1 and GPT-5.6 Sol at a fraction of the price. The company says it scaled reinforcement learning to the multi-trillion-parameter regime for the first time, using Pareto-informed cost penalties that train all reasoning-effort levels in a single run, tripled RL environments, and NVFP4/FP8 quantization-aware training. SWE-2 is available today in Devin Desktop and CLI, with rollout on Devin Web and Fusion.

Hacker News · AIupdated Sep 12, 20:00 UTC · 3d agofirst Sep 10, 15:29 UTC · 6d agoModel release 10 sources HN 58↑ · 15 comments1

German Manufacturer Shrinks Security Alert Response While Protecting 10,000 Endpoints

Vendor case study: a German manufacturer's five-person SOC cut alert triage time using ANY.RUN's cloud sandbox across 10,000 endpoints.

ANY.RUN published a case study in which a five-person security team at an unnamed German manufacturer replaced an air-gapped forensic laptop with its cloud-managed interactive sandbox, protecting roughly 10,000 endpoints and 10,000 users. The vendor claims a median 15 minutes saved per alert, 20-40 daily tasks processed, a 2.5-minute alert-to-isolation target, and a 95% agreement rate between analyst and sandbox verdicts; all figures are vendor-supplied with the customer identity withheld. The writeup also describes detonating a multi-stage phishing chain from a PDF link to a password-protected ZIP to malware execution.

Cyber Security News15:12 UTC · 1h agoIndustry 2 sources

WordPress Security Plugins: How to Choose the Right One

Sucuri's guide breaks WordPress security plugins into hardening, malware scanning, integrity monitoring, and filtering types, and explains how to evaluate and layer them.

The Sucuri guide explains that WordPress security plugins bundle five capabilities - hardening, malware detection, integrity monitoring, activity logging, and application-level filtering - and that plugins run only after WordPress loads, unlike server-level firewalls. It lists leading causes of compromise: outdated plugins and themes, weak or reused credentials, nulled premium software, insecure configuration, and shared-hosting cross-contamination. It concludes with evaluation criteria and a post-installation security checklist for owners without dedicated security teams.

Sucuri BlogSep 5, 03:01 UTC · 11d agoIndustry

Why judgment is emerging as cybersecurity’s defining skill

CyberScoop op-ed argues CISOs should grant AI autonomy based on reversibility and blast radius rather than model confidence, and measure analyst overrides of AI recommendations.

A CyberScoop op-ed contends that as AI takes over analysis and recommendations in security operations, human judgment about context, reversibility and blast radius becomes the defining skill. The author argues autonomy decisions should rest on how reversible and impactful an action is rather than model confidence, citing examples such as patching vendor-certified medical devices and a service account whose 3 a.m. login spikes were normal quarterly-close activity. It also urges leaders to measure analyst approvals, edits and rejections of AI recommendations, and review latency, instead of automation rates or mean time to resolution.

CyberScoopSep 4, 10:00 UTC · 12d agoIndustry1

Predicting Privacy Leakage from Weight Spectral Density

Study shows WeightWatcher spectral metrics like stable rank correlate with membership inference vulnerability, enabling cheaper ML privacy auditing.

The paper tests whether spectral metrics from the heavy-tailed self-regularisation framework can proxy membership inference attack (MIA) vulnerability without training expensive shadow models. On image and tabular classification tasks, stable rank correlates positively with overall MIA success, while Log alpha-Norm correlates negatively at the low false-positive regime. These correlations are stronger than those obtained from the generalisation gap, suggesting weight spectra capture leakage information overfitting measures miss. The authors propose spectral analysis as a scalable direction for privacy auditing.

arXiv cs.CRSep 10, 16:34 UTC · 6d agoResearch

FlowBalance: Verifier-Grounded Self-Improvement from On-Policy Reasoning Experience

FlowBalance is a verifier-grounded self-improvement method that beats FlowRL on Qwen3-4B and Qwen3-8B math reasoning while improving training stability.

FlowBalance calibrates dense self-guidance scores with verifier-derived group advantages: guidance is retained on positive-advantage trajectories, reversed on negative-advantage trajectories, and disabled when rollout groups show no outcome preference. The method exponentially reweights a reference policy via trajectory balance, with guarantees including within-group contrast preservation and a minimum-change reverse-KL characterization. On mathematical reasoning it outperforms FlowRL on Qwen3-4B and Qwen3-8B, trains faster and more stably, avoids direct OPSD's response-length collapse, and shows higher correct-strategy diversity on AIME24.

Hugging Face daily papersSep 2, 20:00 UTC · 13d agoAI research

Gartner: 70% of SOCs will pilot AI agents. Only 15% will see results

Gartner predicts 70% of large SOCs will pilot AI agents by 2028, but only 15% will achieve measurable improvements.

A Gartner report by analysts Craig Lawson and Andrew Davies projects that by 2028, 70% of large SOCs will pilot AI agents for Tier 1 and Tier 2 operations, but only 15% will achieve measurable improvements without structured evaluation. Prophet Security's State of AI in Security Operations 2026 survey found 40% of security teams use AI daily and 56% are evaluating or piloting it. The report offers evaluation questions covering workload reduction, TDIR outcomes, vendor viability, analyst upskilling, and autonomy boundaries to counter AI washing in the market.

Help Net SecuritySep 9, 05:00 UTC · 7d agoIndustry

The Intelligible World of Agents

Recorded Future argues cybersecurity AI agents perform better when reasoning over structured, curated intelligence graphs rather than fragmented alerts or open-source noise.

In a vendor essay, Recorded Future describes how its security agents produced more authoritative analyses after being re-architected to reason primarily over the Recorded Future Intelligence Graph instead of weighting open-source information equally. The author argues agentic decision quality depends mainly on a structured, current operational world model of assets, vulnerabilities, threat actors, detections and organizational context, not on model intelligence itself. The piece further claims frontier model access is commoditizing and that orchestration tooling will converge, making trusted representations of organizational knowledge the durable competitive differentiator.

Recorded FutureSep 10, 00:00 UTC · 6d agoAI safety & security

Unmasking Cloud Identities: From Behavioral Clustering to Automated Detection

Unit 42 clusters behavior of 40,000+ AWS identities from 125 cloud environments to map functional roles and enable lightweight SQL-based detection.

Palo Alto Unit 42 built an unsupervised behavioral clustering model using UMAP and HDBSCAN on AWS CloudTrail logs to map cloud identities to functional roles such as administrators, backup services, security tooling and DevOps. The study analyzed over 40,000 identities across 125 cloud environments over two months. The researchers show that heuristics extracted from the clustering map can be implemented in standard SQL, enabling role classification at scale without running a continuous ML pipeline. The methodology extends to audit logs from other cloud providers, SaaS and Kubernetes.

Palo Alto Unit 42Sep 14, 10:00 UTC · 2d agoResearch

How to Keep Malware’s Rotating Infrastructure From Becoming a Detection Gap

ANY.RUN marketing piece argues SOC detection lags rotating malware and phishing infrastructure, citing a 46-country campaign and 3DBlast kit to promote TI feeds.

ANY.RUN describes how malware and phishing campaigns rotate domains and hosting, making single-IOC blocking ineffective for SOC teams. One investigated phishing campaign spanned 46 countries with 425 kit URLs across 240 hosts, 94% of which were seen for only a single day. A phishing kit dubbed 3DBlast impersonates Microsoft 365 and Google using BitB, AiTM, OAuth device-code phishing and DOM relay techniques. The article is primarily a promotion for ANY.RUN TI Feeds and TI Lookup products.

Cyber Security NewsSep 15, 15:36 UTC · 1d agoIndustry

F5 Bot Defense uses real-time risk scoring to detect fraud and abuse

F5 enhances Distributed Cloud Bot Defense with persistent device identification, real-time risk scoring, and agent-aware policies to manage AI agent traffic.

F5 announced enhancements to Distributed Cloud Bot Defense adding persistent device identification, real-time device risk scoring, risk-based workflow enforcement, and an agent-aware policy framework integrated with the F5 Application Delivery and Security Platform. The features aim to expose multi-account abuse, credential stuffing, and account takeover while allowing trusted AI agents to transact at machine speed. It targets fraud and abuse detection as agentic AI becomes a key interaction channel for sites, apps, and APIs.

Help Net SecuritySep 15, 13:55 UTC · 1d agoTools

SlipSense: Multimodal Tactile Learning for Low-Latency and Generalized Slip Detection

SlipSense fuses a 32x32 piezoresistive array and MEMS accelerometer to detect robotic grip slips within 23.1 ms, generalizing zero-shot across platforms.

SlipSense is a multimodal tactile slip-detection framework built on TacV5, a sensor combining a 32x32 piezoresistive array at 240 Hz and a 3-axis MEMS accelerometer at 8 kHz. It performs modality-specific encoding, intra-sensor fusion, and cross-modal attention with causal temporal prediction at 240 Hz. On a 1.4-million-frame dataset spanning 37 objects it achieves 96.7% Macro F1 with a false-positive rate below 1.6%, detecting 76% of slip events within 23.1 ms. Trained solely on UMI data, it transfers zero-shot to a Tesollo dexterous hand across unseen objects, sensor units, and platforms.

arXiv cs.AI / cs.LG / cs.CLSep 14, 17:23 UTC · 1d agoAI research

The Model Proposes, the Code Disposes: A Pre-Registered Ablation of a Verifier-and-Acceptance Stage in an LLM-Orchestrated Offensive-Security Agent

Pre-registered ablation finds a model verifier stage in an LLM offensive-security agent suppresses findings; removing it eliminated suppression with precision tradeoff.

The paper evaluates a verifier-and-acceptance stage in an LLM-orchestrated offensive-security agent via a pre-registered 20-run confirmatory ablation and a 2x2 factorial study with 40 runs on vulnerable lab targets. Removing the stage eliminated pre-report suppression (median 2 vs 0 findings, p = 0.00003) but reduced model-blinded shipped precision (0.471 vs 0.353, p = 0.0087). Suppression was attributed to the model verifier rather than deterministic acceptance rules, and an instrumented canary recorded zero external contacts in all 60 runs. The full design retained 93.8% of model-adjudicated true candidates but failed its pre-registered non-inferiority floor of 0.90.

arXiv cs.CRSep 14, 17:13 UTC · 1d agoResearch