Search: “security-tooling”

Expanding AI access and cyber defense for federal, state, local, and tribal governments

OpenAI and GSA agreed to provide ChatGPT to federal, state, local, and tribal governments with $0 licenses, 50% off usage, and cyber-defense access.

OpenAI for Government and the U.S. General Services Administration announced a 27-month agreement (October 1, 2026 through December 31, 2028) waiving the $15 per-user monthly license fee and cutting usage costs 50% for federal, state, local, and tribal agencies. More than one million government employees already have ChatGPT access, with eligibility extending across a roughly 23 million-person U.S. public-sector workforce. Every verified government entity is approved for Daybreak Blue cyber-defender access at 50% off, with Daybreak Red available for vulnerability research, exploit validation, and red teaming at standard pricing. The deal builds on the $1 billion Daybreak for Frontline Defenders commitment announced the prior week.

OpenAI News·updated Sep 10, 18:25 UTC · 5d ago·first Sep 10, 07:00 UTC · 6d agoAI industry 3 sources1

Hottest cybersecurity open-source tools of the month: August 2026

August's open-source security roundup highlights NVIDIA SkillSpector for AI agent skill scanning, Future AGI, Chainloop, PentestGPT, and Hazmat agent containment.

Help Net Security's August 2026 roundup covers five open-source tools: NVIDIA's SkillSpector, a scanner that assesses AI agent skills from directories, zips, SKILL.md files, or Git URLs and returns findings and risk scores; Future AGI, an Apache 2.0 platform for tracing, evaluating, simulating, and guardrailing LLM agents; Chainloop, a software supply chain evidence store that produces signed in-toto attestations in CI pipelines; PentestGPT, an agentic penetration testing framework running recon, exploit, and reporting stages; and Hazmat, which runs AI coding agents like Claude Code and Codex inside a separate machine account for containment.

Help Net Security·Aug 26, 00:00 UTC · 21d agoTools

Panzer Ransomware Targets Italian Manufacturers and Telecom Firms With ESXi-Ready RaaS

New Panzer ransomware-as-a-service operation lists Italian firms Doimo Cucine and NTE Italia as victims, offering encryptors for Windows, Linux, FreeBSD, and ESXi.

Panzer, a ransomware-as-a-service operation that surfaced August 5, listed a kitchen manufacturer in Treviso (Doimo Cucine) and a telecommunications engineering firm in Catanzaro (NTE Italia) among alleged victims, claiming 30 GB and 16 GB of stolen data respectively. The group advertises encryptors for Windows, Linux, FreeBSD, and VMware ESXi, a Tox-based affiliate recruitment process with screening, an affiliate dashboard, and an 80/20 revenue split. Neither victim had publicly confirmed the incidents when researcher Andrea Fortuna's report was published, and the group's first access method and payload have not been independently analyzed. Panzer posted victims across 11 countries as claimed Italian ransomware incidents reached 212 by September 6, already above 2025's full-year total of 169.

Cyber Security News·Sep 8, 09:10 UTC · 8d agoRansomware in the wild

The Vulnerability Gap: Why Discovery Is Outrunning Repair

Dark Reading argues AI-accelerated vulnerability discovery and tightening regulation are widening the gap between flaw discovery and repair capacity.

The article argues that AI tooling is increasing the pace at which vulnerabilities are discovered while remediation capacity has not kept up, creating a growing backlog. It frames this widening 'vulnerability gap', combined with a tightening regulatory environment, as an all-hands-on-deck moment for security teams. The piece is analysis and opinion rather than disclosure of a specific flaw.

Dark Reading·Aug 24, 14:00 UTC · 22d agoIndustry

ValleyRAT Backdoor Hides in Signed Adware That Users Add to Antivirus Exclusions

Silver Fox distributes ValleyRAT via signed QN Wallpaper adware, sideloading a malicious libcef.dll into a trusted process to evade defenses.

Kaspersky reports the Silver Fox threat actor disguising the ValleyRAT backdoor (Winos 4.0) inside a modified, signed copy of the QN Wallpaper adware tool, using DLL sideloading to run within a trusted process. The installer disables Windows Defender via the DisableAntiSpyware registry key, adds autorun entries, and elevates via runas when needed; ValleyRAT steals keystrokes, clipboard data, and screenshots and can mark its process critical to trigger BSOD if killed. Kaspersky recorded more than 100,000 ValleyRAT detections affecting over 1,500 unique users in 2026, mostly in China and India, with prior campaigns against Japan, India, and Russia.

The Hacker News·Aug 31, 12:14 UTC · 16d agoMalware in the wild

Authorization Architectures for Tool-Using AI Agents

Review paper proposes an authorization reference architecture for tool-using AI agents, identifying runtime enforcement and delegation bounds as unresolved gaps.

This review examines authorization models for tool-using AI agents that invoke APIs, databases, browsers, and protocols like MCP, arguing every consequential agent action must be traceable to a human principal, bounded by delegation, and contestable. It introduces a principal hierarchy spanning human user, operator/deployer, orchestrator agent, sub-agent, and tool endpoint, and analyzes five layers including credential lifecycle, delegation propagation, runtime enforcement, prompt injection as authorization bypass, and auditability. Drawing on 89 primary sources from 2023-2026, it proposes seven structural requirements, a four-layer reference architecture, and three deployable configurations.

arXiv cs.CR·Sep 14, 17:21 UTC · 1d agoAI safety & security

Learn How to Build Security Operations Ready for AI

Wiz sponsors a webinar on building AI-ready security operations, focusing on attack-path visibility, exposure prioritization, and faster detection-to-remediation workflows.

A contributed piece promotes next week's Wiz webinar, How to Build AI Threat Readiness Across Your Security Operations, featuring a Wiz expert. The session covers using unified security context to separate urgent exposures from noise, understand attack paths across cloud, code, identities, SaaS, and AI services, and connect validated risks to remediation owners.

The Hacker News·Aug 27, 11:56 UTC · 20d agoIndustry

SEMA-GUARD: Semantic and Graph-Based Vulnerability Detection in Assembly Code

SEMA-GUARD uses semantic analysis and graph neural networks to detect vulnerabilities in assembly code, achieving 85.1% accuracy on a Juliet-derived benchmark.

SEMA-GUARD is a framework that detects vulnerabilities in compiled programs when source code is unavailable, targeting malware, firmware, and embedded systems analysis. It enriches control flow graphs with low-level execution semantics including stack manipulations, memory accesses, and data flow. Evaluated on a Juliet Test Suite set compiled to assembly and split into function-level chunks, it achieves 85.1% accuracy and an F1 score of 0.801, outperforming purely statistical or structural approaches.

arXiv cs.CR·Sep 15, 14:35 UTC · 22h agoResearch1

Your Critical Vulnerabilities Might Not Be Your Biggest Risk

Autonomous penetration testing advocates prioritize exploitable attack paths over raw vulnerability severity for continuous security validation.

The article argues that scanner severity scores lack context: a critical flaw behind strong segmentation may be low priority, while a medium flaw on internet-facing systems can provide a foothold chained toward sensitive data. It positions autonomous penetration testing and attack path validation as the execution layer for continuous security validation, replacing point-in-time assessments. The piece is vendor-authored thought leadership rather than incident or vulnerability news.

The Hacker News·Sep 11, 11:30 UTC · 5d agoIndustry1

Self-Verifying Anomaly Detection using Explainable AI for Cybersecurity of DER Networks

ExCYDER framework self-verifies anomaly detection alerts for DER power grids using LightGBM and SHAP, reaching over 98% detection accuracy.

The paper presents ExCYDER, an explainable AI anomaly detection framework for Distributed Energy Resource networks that combines LightGBM with SHAP to validate whether each model decision aligns with its feature-attribution evidence. On a realistic DNP3 dataset it achieved over 98% detection accuracy, 14.5 ms SHAP latency per alert, and confidence deviation within 5%. The self-verifying mechanism distinguishes coherent from inconsistent alerts, improving interpretability and auditability for DER-focused security operations centers.

arXiv cs.CR·Sep 11, 00:19 UTC · 5d agoResearch

Rethinking Indirect Prompt Injection as a Test-Time Search Problem

Researchers frame indirect prompt injection as test-time search, showing added attacker compute improves vulnerability discovery and exploitation against tool-using agents.

The paper models indirect prompt injection as a test-time search over a task-dependent attack surface shaped by the environment, user task, and injection goal. The authors build an agentic attacker with a dedicated search harness that performs reconnaissance, structured strategy reasoning, and adaptive evaluation using victim-agent feedback. Experiments show more attacker test-time compute improves discovery and exploitation of injection vulnerabilities, with explicit strategy management needed to avoid redundant search. The results argue that agentic security evaluations should characterize attacker search procedures and compute budgets rather than treating attack success as budget-independent.

arXiv cs.CR·Sep 3, 21:28 UTC · 12d agoAI safety & security

Attackers use passkey-themed scams to hijack Microsoft 365 accounts

Microsoft tracks ongoing M365 cloud intrusions since May using passkey-themed helpdesk vishing, AiTM phishing, and device-code abuse.

Microsoft Security Research has tracked active cloud intrusions since May in which attackers posing as IT helpdesk staff lured employees with fake passkey/MFA enrollment requests. Attacks used adversary-in-the-middle phishing pages, device-code authentication flows, and Teams messages from compromised accounts. Attackers registered their own MFA methods, enumerated tenants via Microsoft Graph, and accessed SharePoint, OneDrive, and Exchange Online data, throttling activity below 1000 files/emails per hour.

CSO Online·updated 11:58 UTC · 1h ago·first Sep 11, 09:51 UTC · 5d agoThreat actor in the wild 10 sources1

NSA, FBI warns of hackers using AI-generated tools in attacks on critical infrastructure technology

NSA and FBI warn of an active campaign using AI-generated exploit scripts against Siemens S7 PLCs in critical infrastructure sectors.

NSA, FBI and other federal agencies issued an urgent advisory describing an active threat campaign targeting US-based Siemens S7 Series PLCs with AI-generated exploitation scripts disguised as legitimate monitoring tools. Actors use internet scanning to find exposed PLCs in energy, water, and manufacturing sectors, and may be preparing for operational effects. The advisory expands on July warnings of Iran-affiliated hackers targeting PLCs from Siemens, Schneider Electric, Rockwell Automation, and Allen-Bradley.

The Record·Aug 19, 18:01 UTC · 27d agoThreat actor in the wild

How AI could make it harder for governments to use hacking tools

TechCrunch analysis argues AI-driven vulnerability discovery and exploitation may constrain government use of hacking tools and spyware.

The piece reports that AI is proving effective at finding and exploiting software vulnerabilities, which could raise the cost and detectability of government hacking operations. It argues this shift may make it harder for governments to rely on hacking tools and commercial spyware. The analysis also suggests the trend could reignite policy debates around mandated backdoors in consumer devices.

TechCrunch · Security·Aug 31, 15:19 UTC · 15d agoAI policy

Suppliers, logins, and AI tools are all becoming attack paths

Help Net Security·Aug 6, 00:00 UTC · Aug 6, 2026Exploit / PoC in the wild1

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·Sep 4, 15:26 UTC · 11d agoAI safety & security

ActGuard: Pre-execution Action Auditing against Indirect Prompt Injection in LLM Agents

ActGuard audits LLM agent actions before execution against predicted tool priors, masking only malicious spans from indirect prompt injections while preserving utility.

ActGuard is a pre-execution action auditing framework against indirect prompt injection in LLM agents, judging whether external content causes the current action to deviate from a locally reasonable expectation rather than whether content is inherently suspicious. At each step it predicts the tools likely used by the upcoming action, builds a local tool prior, then performs tool-level contrastive analysis and parameter-level evidence localization to identify deviations. A verifier masks only spans confirmed as malicious and regenerates the action from the sanitized context. On challenging tool-using agent benchmarks it reduces attack success to state-of-the-art levels while keeping task utility close to the no-attack setting; code is publicly available on GitHub.

arXiv cs.CR·Sep 14, 03:47 UTC · 2d agoAI safety & security

AI Coding Tools Now a Prime Target for Threat Actors, Google Warns

Google Threat Intelligence Group warns threat actors increasingly target AI coding tools and proprietary AI data, with UNC6780's Dustmaker enabling large-scale supply chain compromises.

Google Threat Intelligence Group's September 8 report says AI-assisted coding tools have become prime targets, contributing to large-scale software supply chain compromises in 2025 and early 2026. Financially motivated group UNC6780 used its Dustmaker credential stealer to extract tokens from GitHub Actions runner memory and compromise packages across PyPI, npm, and Docker Hub, then sold harvested AI tool credentials to other criminals. Chinese nation-state actor UNC6508 conducted espionage against proprietary AI research at North American academic, medical, and military institutions, while extortion gangs stole models, prompts, and source code in Q2 2026. GTIG also documented agentic attacker experimentation, including an autonomous multi-agent credential harvesting campaign built in under six hours and a 'Recon' C2 framework managing over 23,800 harvested secrets.

Infosecurity Magazine·Sep 8, 12:02 UTC · 8d agoThreat actor in the wild 2 sources1

Hackers Impersonate IT Support on Microsoft Teams to Take Control of Employee PCs

Microsoft warns of a human-operated campaign where attackers pose as IT support in Teams to gain remote PC control and reach domain controllers.

Microsoft Threat Intelligence observed attackers abusing Microsoft Teams external collaboration to impersonate IT/helpdesk staff, persuading employees to grant screen control via Quick Assist or RMM tools. Operators deploy malicious MSI packages via silent msiexec, run encrypted JavaScript implants through portable Node.js, and persist via EdgeUpdate Run keys or Startup folder entries. The Node.js backdoor uses HTTPS long-polling C2, captures screenshots, enumerates Active Directory, and moves laterally over WinRM (TCP 5985) to domain controllers and certificate authorities. Initial access maps to MITRE ATT&CK T1566.003 (Spearphishing via Service); no Teams vulnerability is exploited.

GBHackers·Sep 8, 13:28 UTC · 7d agoPhishing & fraud in the wild

What researchers learned about building an LLM security workflow

Oslo and FFI researchers show structured agentic workflows lift LLM alert-triage accuracy from 0% to about 93% on malicious cases.

Researchers at the University of Oslo and the Norwegian Defence Research Establishment tested GPT-5-mini, Claude 3 Haiku, Qwen3:30B, and Gemma 3:27B on alerts from the AIT Log Data Set V1.1; given only alert descriptions and log summaries, all four models correctly flagged zero percent of true-positive cases involving reconnaissance, brute-force logins, and initial access. Wrapping the same models in a workflow with constrained SQL queries over Suricata logs, an evidence summarizer, and a verdict stage with revision loops raised malicious-case accuracy to an average of 93 percent, with GPT-5-mini identifying every malicious case across 100 runs. The authors flag it as a proof-of-concept on one synthetic scenario and note models skewed conservative on benign alerts, with GPT-5-mini marking every benign case uncertain.

Help Net Security·Aug 24, 04:21 UTC · 23d agoAI research1

How to secure edge AI in customer-owned environments

Microsoft outlines security architecture guidance for edge AI, urging runtime attestation, artifact provenance, and deterministic mediation of model actions.

Microsoft details how edge AI shifts trust responsibilities to customers operating their own infrastructure, where prompt injection, model tampering, and malicious firmware updates can occur alongside model weights, credentials, and physical-system access. The guidance recommends verifying runtimes with attestation, verifying AI artifacts with provenance, and constraining model actions through a deterministic mediator outside the model. It also covers new exposure surfaces from MCP, multi-agent systems, and computer-use agents running in disconnected or hostile edge environments.

Microsoft Security Blog·Sep 4, 19:10 UTC · 11d agoAI safety & security

Propagation Model for SSC attacks: Why SBOM (tools) don't tell the whole truth

Study shows open-source SBOM tools only cover structural exposure and vulnerability presence, missing code reachability and taint-path analysis stages.

An arXiv paper proposes a four-stage propagation model for software supply chain attack effects and empirically evaluates four open-source SBOM tools against it using three projects and the Log4j vulnerability as the test case. Current SBOM tools systematically support only Stage 1 (structural exposure) and Stage 2 (vulnerability class presence), while Stage 3 (code reachability) and Stage 4 (taint path analysis) require capabilities absent from the SBOM ecosystem. The authors argue propagation-centred SSC security research is needed to prevent cyber risk from evolving into systemic risk.

arXiv cs.CR·Sep 4, 17:31 UTC · 11d agoResearch1

Hackers Turn Windows Shadow Copies Into a Tool for Credential Theft and Ransomware

Attackers abuse Windows VSS shadow copies to delete recovery points before ransomware and to extract NTDS.dit/SAM credentials, demanding context-aware detection.

Threat actors are weaponizing the Volume Shadow Copy Service (VSS) for two purposes: destroying local recovery points via vssadmin.exe, wmic.exe, diskshadow.exe, wbadmin.exe, and bcdedit.exe before encryption, and accessing static copies of locked files such as NTDS.dit and SAM for credential theft. Ransomware families tied to shadow-copy removal include Akira, Black Basta, BlackCat, Conti, LockBit, Qilin, RansomHub, REvil, Ryuk, and WannaCry. Huntress's analysis of the Nightmare-Eclipse tool showed the BlueHammer technique chaining a Windows Defender timing issue with a VSS snapshot to dump the SAM database and decrypt NT hashes. Defenders should correlate VSS operations with parent process, hive access, and subsequent encryption activity, and maintain immutable off-host backups.

GBHackers·Sep 15, 05:51 UTC · 1d agoResearch in the wild1

Understanding the Security Boundary of Obfuscation-based On-Device LLM Protection

Researchers formalize obfuscation primitives for TEE-protected on-device LLMs and show a Collapse attack breaks ArrowCloak, TSQP, and LoRO, then extend the boundary.

The paper formalizes obfuscation primitives for TEE-Shielded LLM Partition (TSLP) schemes that offload computationally intensive layers from a Trusted Execution Environment to external GPUs. A novel primitive-guided attack, Collapse, demonstrates a shared vulnerability in prominent published methods including ArrowCloak (Security'25), TSQP (S&P'25), and LoRO (NeurIPS'25). The authors then introduce two new obfuscation primitives and integrate them with existing constructs to formulate an extended security boundary (O_ext).

arXiv cs.CR·Sep 9, 12:51 UTC · 7d agoAI safety & security

Attack Chains, Not Just Attack Surfaces: Why Testing Individual Techniques Misses the Point

Filigran introduces Attack Chaining in OpenAEV to continuously simulate multi-stage attack paths, exposing gaps that isolated MITRE ATT&CK technique testing misses.

Filigran announced Attack Chaining, a new scenario type in its OpenAEV platform that links individual techniques into automated, continuously-run multi-stage attack paths, using each step's real output (credentials, tokens, open ports) to branch dynamically toward a final objective. The article cites Filigran's State of Threat Management report, in which 93% of security leaders reported a business-impacting cyberattack in the past 12 months, 88% said AI accelerates attackers, and 84% blamed siloed tools and disconnected testing. The 2025 DGFiP breach is cited as an example where individually survivable weaknesses chained into a major intrusion. The feature includes conditional chaining logic, live attack path mapping, structured findings for identifying chokepoints, and predefined scope and safety guardrails.

The Hacker News·Sep 15, 11:26 UTC · 1d agoTools

The Security Feature Location Problem

Researchers formalize security feature location, mapping code regions to security features like authentication and encryption to audit implementations.

The paper introduces security feature location: the task of relating code locations to implemented security features such as authentication and encryption. It argues the task enables developers to understand security implementations and assess whether intended security properties are actually enforced in software systems.

arXiv cs.CR·Sep 4, 08:59 UTC · 12d agoResearch

Edge infrastructure under siege: what two independent datasets reveal about who's exploiting your perimeter

Joint Tenable-SentinelOne analysis of 93 CVE-actor attribution pairs shows nation-state and criminal groups independently converge on the same edge infrastructure.

Tenable and SentinelOne jointly analyzed 93 CVE-actor attribution pairs covering exploitation of perimeter devices. The data shows state-sponsored and financially motivated actors independently target the same edge products from Ivanti, Fortinet, and Palo Alto Networks. The findings challenge the narrative that edge exploitation is exclusively a China-nexus nation-state problem, showing a broader shared attack surface.

Tenable Blog·Aug 26, 13:00 UTC · 21d agoThreat actor in the wild

Microsoft Copilot reveals secret input that allowed it to be hacked

Microsoft disclosed a hidden input in Copilot that let attackers steal passwords from users who clicked a crafted link.

Microsoft revealed that Copilot contained a secret, undocumented input parameter that allowed the assistant to be compromised. Attackers could abuse the hidden input to steal passwords when a target clicked a malicious link. The disclosure highlights hidden-parameter risks in widely deployed AI assistants.

Ars Technica · Security·Aug 18, 13:00 UTC · 29d agoAI safety & security in the wild1

Mars Security Debuts Automated Threat Engine Processing Live Cyber Intelligence Into Validated Rules Within Minutes

Mars Security launches Real-Time Intel-Based Detection, converting threat intelligence advisories into validated, ATT&CK-mapped detection rules within minutes for SOCs.

Mars Security, an autonomous threat hunting and detection engineering platform founded by former offensive security operators, announced Real-Time Intel-Based Detection. The capability ingests advisories from sources like CISA, Mandiant, Unit 42, and Microsoft Threat Intelligence, maps indicators to MITRE ATT&CK, and authors native query logic across connected infrastructure including CrowdStrike Falcon, Wiz, Splunk, Sysmon, identity providers, Snowflake, and Databricks. Every rule is backtested against 30 days of historical telemetry to quantify false positives before analyst approval and one-click deployment. The feature is free for existing customers and available via AWS Marketplace.

CSO Online·Sep 8, 15:05 UTC · 7d agoTools1