Search: “targeted-attacks”

Pick Your Poison: Learning to Select Poison Sets for Stronger LLM Backdoor Attacks

SAILS learns to select poison sets for LLM backdoor attacks, showing attack success ranges 3% to 80% at fixed poison counts across LLaMA-3-8B settings.

The paper shows existing backdoor evaluations that randomly sample a fixed number of poisoned examples severely underestimate worst-case vulnerability: across three LLaMA-3-8B settings, attack success ranges from 3% to 80% depending only on which poison set is chosen. SAILS formalizes poison selection as oracle-budgeted set optimization, learning a set scorer from a few hundred finetune-and-evaluate runs to rank millions of candidate sets and audit a small shortlist. It improves held-out attack success by 30 percentage points over the strongest influence baselines and transfers from small-scale to full-scale finetuning, extending to code-generation, agentic, and API-only backdoors.

arXiv cs.CR·Sep 14, 04:44 UTC · 2d agoAI safety & security 2 sources

Top 10 Best Mobile Threat Defense (MTD) Solutions in 2026

Roundup of 2026 mobile threat defense tools recommends Zimperium and Lookout for targeted-attack detection and Defender for Endpoint for Microsoft shops.

This guide ranks ten mobile threat defense solutions, recommending Zimperium and Lookout for on-device detection against targeted users such as executives and journalists, and Microsoft Defender for Endpoint mobile for organizations already licensing Microsoft 365 E5. It explains that MDM enforces configuration while MTD detects attacks, and that mobile phishing now arrives via SMS, messaging apps and QR codes rather than email. It also highlights mercenary spyware and zero-click exploits as shifting requirements for high-risk users, referencing Apple's threat-notification program and Lockdown Mode.

Cyber Security News·Sep 9, 07:50 UTC · 7d agoIndustry

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

When AI infrastructure becomes the target: Securing gateways and control points

Microsoft Threat Intelligence details attacks on exposed AI workloads exploiting LiteLLM gateways for credential harvesting, persistence, and cryptomining.

Microsoft Threat Intelligence examines attacks targeting exposed AI workloads, including exploitation of LiteLLM gateway deployments. Post-exploitation activity includes credential harvesting, establishing persistence, and cryptomining. The post urges defenders to secure AI infrastructure gateways and control points; the available text does not name threat actors, CVEs, or provide IOCs.

Microsoft Security Blog·Aug 26, 16:43 UTC · 20d agoExploit / PoC in the wild

HYDRA: Quantifying Botnet Resource Thresholds for Efficient Link-Flooding Attacks on LEO Satellite Networks

HYDRA models link-flooding attacks on LEO satellite constellations as botnet minimization, matching prior disruption with 34% fewer bots and 23% less traffic.

HYDRA formulates link-flooding attack variants against LEO constellations such as Starlink and Kuiper as botnet minimization problems, quantifying the smallest bot subset and traffic allocation needed to disrupt communications between targeted geographic areas. Under matched stealth constraints it matches the ICARUS attack's disruption using 34% fewer bots and 23% less aggregate traffic, sustaining over 97% attack success as topology evolves. The framework also evaluates five mitigations, including routing diversification, ingress policing, distance-based constraints, source throttling, and botnet attrition.

arXiv cs.CR·Sep 14, 15:00 UTC · 1d agoResearch

Confusedpilot Attack Targets Ai

ConfusedPilot attack exploits Microsoft 365 Copilot's retrieval pipeline to expose confidential enterprise data in AI responses.

ConfusedPilot targets Microsoft 365 Copilot's retrieval-augmented generation pipeline, potentially causing the assistant to surface confidential enterprise content in generated responses. Researchers disclosed the technique as a Copilot data confidentiality flaw affecting search and caching behavior. It highlights the emerging attack surface in enterprise AI assistants that access corporate data stores.

Infosecurity Magazine·Aug 16, 00:00 UTC · Aug 16, 2026AI safety & security in the wild

Attackers Target miniOrange SAML Flaws That Can Grant WordPress Admin Access

Attackers are exploiting two unauthenticated WordPress auth bypasses (CVE-2026-61979, CVE-2026-15981, max CVSS 9.8) in miniOrange SAML SSO to gain admin sessions.

Patchstack disclosed two flaws in the Xecurify miniOrange SAML 2.0 Single Sign On WordPress plugin: CVE-2026-15981 (CVSS 9.8) accepts malformed signatures because mo_saml_validate_signature() loosely checks the tri-state result of openssl_verify(), and CVE-2026-61979 (CVSS 8.1) enables privilege escalation via signature algorithm confusion. Both let unauthenticated attackers sign in as any WordPress user, including administrators; fixes shipped in Standard edition versions 17.0.6 and 17.0.5. DigitalOcean observed an attacker using the bypass to obtain an admin session cookie, opportunistic scanning is underway from six IP addresses, and PoC chaining code is public.

The Hacker News·Aug 25, 08:34 UTC · 22d agoExploit / PoC in the wildCVE-2026-61979CVE-2026-15981

SilkParasite Espionage Campaign Targets Central Asian Governments with Five New RATs

Bitdefender reports SilkParasite, a China-nexus espionage cluster targeting Central Asian governments with seven RATs, five newly documented, delivered via spearphished RAR archives.

Bitdefender Labs assesses with medium confidence that SilkParasite, first discovered in late 2025, is a China-nexus cluster targeting government bodies in Uzbekistan, Turkmenistan, Kyrgyzstan, Tajikistan, Kazakhstan, and Georgia. Attacks use password-protected RAR archives with malicious Office documents, macro-triggered DLL sideloading, and checks for running Kaspersky AV before execution. The arsenal spans seven RAT families in .NET, C++, Go, and JavaScript with plugin architectures and diverse C2 channels including Google Drive and HTTP cookie/ETag headers; roughly 65 DriveSilkRAT infections were observed, mostly in Asia. Ties to China include BLOODALCHEMY (a Deed RAT/ShadowPad descendant) and an improved SpiceRAT used by SneakyChef, with traces of AI-assisted development in the tooling and lures.

The Hacker News·Aug 20, 05:47 UTC · 27d agoThreat actor in the wild

AI-Generated Exploit Scripts Target Siemens S7 PLCs in U.S. Critical Infrastructure

NSA, CISA, FBI, DOE and EPA warn that actors use AI-generated Python scripts to exploit internet-exposed Siemens S7 PLCs at U.S. critical infrastructure.

A joint advisory from NSA, CISA, FBI, DOE and EPA describes an active threat in which AI-generated exploit scripts disguised as legitimate monitoring tools target Siemens S7 Series PLCs (S7-200 through S7-1500, including F-series safety controllers). The actors use Censys and ZoomEye scanning to find internet-exposed, outdated PLCs and a custom Python script using snap7 libraries over the S7comm protocol for initial access, credential access and denial of service; no attribution was given. Targeted sectors include Critical Manufacturing, Energy, Water and Wastewater, Chemical, Food and Agriculture, and Commercial Facilities, with potential for process disruption and cascading impacts. A related Dream report details a near-autonomous AI-agent campaign (July 1-4, 2026, 12 waves) against Taiwan government entities, using Hermes and OpenClaw agents with eight parallel sub-agents to crack 85 accounts via password spraying and exfiltrate over 2,564 personnel records, SSO client secrets and database credentials.

The Hacker News·Aug 21, 05:39 UTC · 26d agoExploit / PoC in the wild1

New Interrupt Injection Attack Can Bypass Spectre v2 Defenses on Intel and AMD CPUs

The Hacker News·Aug 8, 10:51 UTC · Aug 8, 2026VulnerabilityCVE-2023-20569

Cloud and SaaS Environments Now Top Targets for Attackers

Infosecurity Magazine·Aug 4, 11:30 UTC · Aug 4, 2026Ransomware

Cybercriminals Turn to Indirect Prompt Injection Attacks

Proofpoint reports cybercriminals are now adopting indirect prompt injection attacks against AI-powered systems.

Proofpoint's threat intelligence reports that cybercriminals have turned to indirect prompt injection attacks, extending the technique from a research concern into observed criminal tradecraft. The article is available by title only, so specific victims, campaigns, and targets are not detailed here.

Proofpoint Threat Insight·Aug 13, 13:25 UTC · Aug 13, 2026AI safety & security in the wild

A revisit of remote Spectre attacks on Cloudflare Workers

Cloudflare details its 2024-2025 reassessment of remote Spectre attacks on Workers, covering new attack primitives and hardened defenses.

Cloudflare reassessed the feasibility of remote Spectre attacks against its Workers serverless infrastructure across 2024 and 2025. The write-up describes new attack primitives including Spectre gadgets, remote timers, and techniques for achieving co-location with victim workloads. It also explains new defenses that further harden Cloudflare Workers against speculative-execution side channels.

Cloudflare Blog·Aug 19, 16:00 UTC · 27d agoResearch

Three-quarters of Ransomware Attacks Target Mid-Market Firms

Black Kite research finds roughly 75% of ransomware attacks target mid-market firms, with manufacturers hit most often.

Attack-surface management vendor Black Kite published findings that about three-quarters of ransomware attacks target mid-market organizations. Manufacturing is the sector most likely to be attacked. The report frames mid-market companies as the sweet spot for ransomware operators.

Infosecurity Magazine·Aug 18, 10:00 UTC · 29d agoRansomware in the wild

Inside 90 days of attacks on AI infrastructure

Wiz honeypots recorded 90 days of active campaigns attacking LiteLLM, MCP servers, and AI frameworks via RCE, blind prompt injection, and credential theft.

Wiz deployed AI infrastructure honeypots and observed active attack campaigns over a 90-day window. Attackers targeted LiteLLM, MCP servers, and popular AI frameworks using techniques including remote code execution, blind prompt injection, and memory credential theft. The findings show exposed AI infrastructure is being actively targeted in the wild.

Wiz Blog·Aug 27, 16:33 UTC · 19d agoAI safety & security in the wild

Threat Matrix: Mapping threats across cloud web applications

Microsoft released a Cloud Web Applications Threat Matrix, a MITRE ATT&CK-aligned framework mapping threats to cloud-hosted web apps and serverless platforms.

Microsoft introduced the cloud web applications threat matrix, which organizes attack techniques for cloud-hosted web apps and serverless platforms using MITRE ATT&CK tactics, from resource development through impact. The framework covers attack paths spanning application code, managed runtimes, workload identities, and deployment pipelines, cataloging techniques such as subdomain takeover, code injection in connected repositories, compromised registry images, exposed admin interfaces, and serverless trigger injection. It builds on Microsoft's earlier Kubernetes and storage services matrices to help defenders identify visibility gaps, prioritize hardening, and plan investigations in cloud-native environments.

Microsoft Security Blog·Sep 9, 21:30 UTC · 6d agoTools

Hackers Frequently Target Healthcare and Finance Orgs

A new Huntress survey indicates threat actors frequently target healthcare organizations and banks because of the highly personal data they hold.

Huntress published survey findings indicating that healthcare organizations and banks are frequent targets for threat actors. The piece attributes this to the highly personal information these sectors handle. The article is framed around cyberattack readiness rather than a specific incident.

Huntress·Sep 1, 14:00 UTC · 14d agoIndustry

InceptionRAG: Stealthy Poisoning Attack Against Retrieval-Augmented Generation

InceptionRAG fragments malicious payloads into dormant passages that trigger LLMs to self-deduce misinformation via multi-hop reasoning, bypassing existing RAG poisoning defenses.

Researchers introduce InceptionRAG, a stealthy corpus poisoning attack against retrieval-augmented generation that splits a malicious payload into a chain of individually harmless dormant passages. When retrieved together, the passages induce LLMs to self-deduce target misinformation through multi-hop reasoning, achieving over 80% attack success rate across three datasets and three LLMs under rigorous adversarial constraints. A zeroth-order suffix optimization (ZOSO) method automates authoritative suffix generation in black-box settings. The authors also propose HODOR, a document isolation defense that decouples adversarial logical dependencies.

arXiv cs.CR·Sep 15, 08:22 UTC · 1d agoResearch

Security leaders must prepare for likely threats, not sensationalized agentic attacks

CSO opinion argues agentic AI attacks mostly exploit mundane vulnerabilities, urging defenders to train on realistic threat profiles rather than sensational containment breaches.

An opinion piece contends recent reports of AI models 'breaching containment' at OpenAI, Anthropic, and Meta overshadow the more likely risk: AI agents exploiting conventional unpatched flaws and insecure APIs. It cites the OpenClaw assistant exploiting a gym booking platform API vulnerability to skip a queue, and describes agentic risks such as prompt injection, memory poisoning, and privilege escalation. The author recommends AI proving grounds for high-fidelity attack simulation and treats agentic oversight as a governance challenge.

CSO Online·Sep 8, 09:00 UTC · 8d agoAI safety & security

The AI Attack Surface: How Threat Actors Abuse Trusted AI Platforms

Huntress explains how threat actors abuse trusted AI platforms as an attack surface for malware delivery and data theft.

Huntress's post describes threat actors targeting the AI attack surface, abusing trusted AI tools and platforms to deliver malware and steal data. Using legitimate AI services helps attacker activity blend into normal traffic and evade detection. The article frames AI platforms as an increasingly exploited part of the enterprise attack surface that defenders should monitor.

Huntress·Aug 27, 04:00 UTC · 20d agoAI safety & security in the wild

Misleading the Planner through Deceptive Resumes: Registration-Time Injection in Centralized Multi-Agent Systems

Researchers demonstrate registration-time prompt injection in centralized LLM multi-agent systems, dropping GAIA task success from 84.31% to 37.25%, and propose DescGuard defense.

The paper identifies a registration-time injection channel in centralized LLM multi-agent systems where third-party worker agent descriptions are trusted by the planner before any user instruction arrives. Analyzing 32,000 descriptions from three public agent marketplaces, at least 23.35% contain content outside the four defined description fields. Eight description-manipulation attack strategies targeting task decomposition, capability grounding, and subtask specification cut GAIA task success from 84.31% to 37.25% and increased token consumption or execution time by over 111%, persisting across two MAS implementations, six planner LLMs, and four evaluators. The proposed DescGuard defense filters descriptions to worker-scoped interface information and restores metrics toward baseline without modifying workers, planner, or orchestration logic.

arXiv cs.CR·Sep 14, 13:06 UTC · 1d 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

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 · 20d agoThreat actor in the wild

UNC6671 Vishing Attacks Target Personal Phones to Steal SaaS Data

Google and Mandiant attribute vishing-based SaaS data extortion attacks to UNC6671, now operating under the Redact, Pink, Helix, and Falcon brands.

Google Threat Intelligence Group and Mandiant track extortion group UNC6671, which uses vishing calls impersonating IT help desks to lure employees to adversary-in-the-middle phishing pages that capture credentials, MFA tokens, and session tokens. The group then registers adversary-controlled MFA devices, pivots through identity providers into Microsoft 365, Okta, and other SaaS applications, and runs automated Python and PowerShell exfiltration scripts. UNC6671 has rotated through extortion brands including BlackFile, Redact, Pink, Helix, and Falcon, and Google tracked over $10.6 million in Bitcoin payments between January 7 and May 12, 2026, with initial demands exceeding $3 million. The actor has hit dozens of organizations in North America, Australia, and the UK, shifting toward high-value financial and legal firms in July 2026.

The Hacker News·updated Sep 7, 15:51 UTC · 8d ago·first Sep 7, 15:39 UTC · 8d agoThreat actor in the wild 2 sources1

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.CR·Sep 14, 04:28 UTC · 2d 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