Search: “exploit-generation”

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

Poison set selection swings LLM backdoor attack success from 3% to 80%; SAILS boosts held-out success by 30 points.

The paper shows that random poison set selection severely underestimates worst-case backdoor vulnerability: across three LLaMA-3-8B settings with fixed model, clean data, and poison count, attack success ranges from 3% to 80% depending only on which poison set is chosen. The authors formalize poison selection as oracle-budgeted set optimization and introduce SAILS, which learns a set scorer from a few hundred finetune-and-evaluate runs, ranks millions of candidate sets, and audits a shortlist. SAILS improves held-out attack success by 30 percentage points over the strongest influence baselines, transfers from small-scale to full-scale finetuning, and extends to code-generation, agentic, and API-only backdoors.

Hugging Face daily papers·updated Sep 14, 04:44 UTC · 2d ago·first Sep 13, 20:00 UTC · 2d agoAI safety & security 2 sources1

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Linux Kernel ZcopyReaper Vulnerability Lets Local Attackers Gain Root Privileges

Linux kernel RDS zero-copy flaw CVE-2026-43502 (ZcopyReaper) lets unprivileged local users gain root; fix in 7.1-rc3, public PoC published.

CVE-2026-43502, dubbed ZcopyReaper, is a Linux kernel local privilege escalation flaw in the RDS zerocopy send path, present since kernel 4.17, allowing unprivileged local attackers to gain root. NebuSec researcher Yuan Tan demonstrated root escalation on openSUSE kernel 6.4.0-150600.23.100; the fix landed in commit 44b550d88b26 with Linux 7.1-rc3 the first patched mainline release. Exploitation requires CONFIG_RDS and CONFIG_RDS_TCP but not unprivileged user namespaces, and PoC exploit material is publicly released alongside more than 20 other exploitable 2026 kernel CVEs.

GBHackers·Sep 15, 08:18 UTC · 1d agoExploit / PoCCVE-2026-43502CVE-2026-43501CVE-2026-43074+4 CVEs1

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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

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New ZcopyReaper Linux Kernel Vulnerability Enables Privilege Escalation Attacks

ZcopyReaper (CVE-2026-43502) lets unprivileged local attackers reach root on Linux via an RDS zero-copy cleanup flaw dating to kernel 4.17.

CVE-2026-43502 is a lifetime-management error in rds_message_purge() that mishandles zero-copy sends before socket attachment, corrupting kernel memory and enabling local privilege escalation without capabilities or user namespaces. NebuSec demonstrated the exploit on openSUSE kernel 6.4.0-150600.23.100; vulnerable systems need CONFIG_INET, CONFIG_AIO, CONFIG_RDS, and CONFIG_RDS_TCP. The fix landed in mainline commit 44b550d88b26 (Linux 7.1-rc3) with backports to Ubuntu 7.0.0, 6.8.0, and 5.15.0 kernels and multiple Debian branches. NebuSec also released public exploits for 20 additional Linux kernel vulnerabilities in its CyberMeowfia repository.

Cyber Security News·Sep 14, 13:29 UTC · 1d agoVulnerabilityCVE-2026-43502

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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

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[webapps] Langflow 1.8.4 - Path Traversal to Remote Code Execution

A path traversal to remote code execution exploit for Langflow 1.8.4, a popular LLM application builder, was published on Exploit-DB.

Exploit-DB lists a proof-of-concept exploit chaining path traversal to remote code execution in Langflow 1.8.4, an open-source tool used to build LLM applications and agents. The chain allows an attacker to write arbitrary files outside the intended directory and achieve code execution on the host. The provided text does not include a CVE identifier or reports of exploitation in the wild, but RCE in a widely deployed AI tooling product is notable for defenders.

Exploit-DB·Aug 31, 00:00 UTC · 16d agoExploit / PoC1

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Just a rumour of a bug is enough to find a security exploit these days

Commentary argues that an unverified rumor of a software bug is now enough for researchers or attackers to develop a working exploit.

A short blog note reflects on how modern exploit development has accelerated to the point that even a mere rumor of a vulnerability can be enough to locate and weaponize a bug. The piece is commentary on the current state of security research and attacker trends rather than a disclosure of a specific flaw.

Lobsters · security·Aug 28, 20:23 UTC · 18d agoIndustry

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Evooo1Bot Linux Botnet Exploits Known Flaws to Turn Edge Devices Into SOCKS5 Proxies

Fortinet researchers documented Evooo1Bot, a new Mirai-derived Linux botnet active since July 2026 that exploits known edge-device flaws to build SOCKS5 proxy networks.

Fortinet FortiGuard Labs identified Evooo1Bot, a previously undocumented Linux botnet built on the leaked Mirai source code, active in the wild since July 2026 and targeting internet-facing edge devices. It exploits numerous known CVEs in routers and devices from D-Link, Tenda, Telesquare, Zyxel, Hikvision, Atlassian Confluence, WSO2, TP-Link, NETGEAR, and others, delivering a bot binary via a wget.sh loader from 91.92.40.118 that clears bash history. The bot offers encrypted C2 on port 443, SSH brute-force scanning, credential sniffing, DDoS over DNS/TCP/UDP, an HTTP exploit dispatcher, and converts infected hosts into SOCKS5 proxies for anonymizing follow-on operations.

The Hacker News·Aug 17, 09:29 UTC · Aug 17, 2026Malware in the wildCVE-2007-3010CVE-2016-6277CVE-2018-14558+15 CVEs

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Scam Attacks Taking Advantage of the Popularity of the Generative AI Wave

Unit 42 finds about 225 generative AI-themed domains registered daily since ChatGPT's launch, with nearly 29 percent suspicious, fueling scams and PUP delivery.

Palo Alto Networks analyzed new domain registrations containing generative AI keywords such as chatgpt, prompt, and sora since ChatGPT's November 2022 launch, observing around 225 GenAI-related registrations per day. About 28.75 percent of these domains are suspicious, a rate 22 times higher than for general new domains, with registration spikes aligning with milestones like Bing ChatGPT integration, the GPT-4 release, new GPTs, and OpenAI's Sora announcement. Over 72 percent of the domains use gpt or chatgpt keywords, and gpt domains show a 76 percent suspicious rate. Case studies cover PUP delivery, spam distribution, and monetized domain parking, with 35 percent of traffic to these domains directed at suspicious ones.

Palo Alto Unit 42·Aug 17, 12:47 UTC · Aug 17, 2026Phishing & fraud in the wild1

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Towards Scalable and Cost-Efficient Vulnerability Detection: A Study on Automatic Query Generation

A study finds LLM-synthesized CodeQL queries improve average F1-score by 82% over baseline queries, offering scalable vulnerability detection versus direct LLM scanning.

Researchers conducted an empirical study evaluating whether LLMs can synthesize executable CodeQL queries from National Vulnerability Database vulnerability data. LLM-generated queries significantly enhanced baseline CodeQL suites, yielding an 82% improvement in average F1-score across a diverse set of real-world vulnerabilities. A cost-benefit analysis shows direct LLM-based scanning of entire repositories is often computationally and financially prohibitive, while LLM query synthesis offers a scalable and cost-effective alternative for large-scale vulnerability detection.

arXiv cs.CR·Sep 9, 16:31 UTC · 6d agoResearch1

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[webapps] Grav CMS 2.0.7 - RCE

A proof-of-concept exploit for remote code execution in Grav CMS 2.0.7 has been published on Exploit-DB.

Exploit-DB lists a public proof-of-concept exploit for a remote code execution vulnerability in Grav CMS 2.0.7. The listing is for web applications and provides code defenders can use to reproduce the issue. No exploitation in the wild or CVE assignment is stated in the listing.

Exploit-DB·Sep 1, 00:00 UTC · 15d agoExploit / PoC

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Attackers Exploit Critical Langflow and Rails Flaws in Credential

VulnCheck reports active exploitation of critical Langflow CVE-2026-0768 and Rails CVE-2026-66066 for credential harvesting, with detections rising to 360.

VulnCheck observed active exploitation of CVE-2026-0768 (CVSS 9.8) in Langflow and CVE-2026-66066 'KindaRails2Shell' (CVSS 9.5) in Ruby on Rails, with detections rising from 50 on August 30, 2026 to 360 by September 1. The Rails flaw allows unauthenticated arbitrary file reads, leaking secret_key_base, Rails master key, database passwords, cloud credentials and API tokens, ultimately enabling RCE; the patch still leaves the variation-key Marshal deserialization RCE gadget functional. Observed chains include a Python credential harvester with SimpleHelp remote access via CVE-2026-5027, and weaponization of CVE-2025-3248 to enlist hosts into an XMR mining botnet after disabling auditd. More than 7,100 exposed vulnerable Ruby on Rails instances and over 15,000 successful exploitation attempts across three Langflow flaws were recorded.

The Hacker News·Sep 1, 07:23 UTC · 15d agoExploit / PoC in the wildCVE-2026-0768CVE-2026-66066CVE-2026-0769+2 CVEs1

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CiteShade: Citation Laundering in Multi-Source Retrieval-Augmented Generation and Its Counterfactual Defense

CiteShade attack makes RAG models cite trusted sources for attacker-chosen wrong answers, raising wrong-answer rate from 0.01 to 0.68.

CiteShade is presented as the first citation laundering attack against multi-source retrieval-augmented generation: an attacker controlling a single source induces a wrong answer falsely attributed to a trusted source, even while correct evidence remains in context. The attack is formalized via three necessary conditions (retrieval, generation, citation) constructible without any instructions, raising wrong-answer rate from 0.01 to 0.68 on multi-hop QA, with source deletion confirming the malicious source as causal driver. Vulnerability tracks a model's citation propensity rather than scale, reaching CLR 0.84 with explicit instruction and 0.64 without on the most citation-prone model. Perplexity filtering and citation-support checking prove insufficient; the authors propose a counterfactual defense verifying which source actually drove the answer.

arXiv cs.CR·Sep 14, 14:41 UTC · 1d agoAI safety & security1

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BenchShield: Formal Model-Backed Instrumentation for Reward Integrity in LLM-Agent Evaluation Infrastructure

BenchShield uses lifecycle-model-backed instrumentation to detect reward hacking in LLM-agent benchmarks, lifting full-chain recall to 77-100% at up to 65% lower cost.

The framework grounds reward-hacking detection in a finite lifecycle model of an evaluation's reward-relevant events, combining a static phase-aware taint analysis with runtime infrastructure-side evidence attribution. Evaluation used a human-labeled corpus of 456 adjudicated trajectories drawn from more than 31,000 public agent runs across three benchmarks. BenchShield improves full-chain recall from 23-94% to 77-100% and same-vector coverage from 16-56% to 43-78%, cuts per-task cost by up to 65%, and achieves 96% accuracy detecting reward hacking at runtime.

arXiv cs.CR·Sep 10, 03:10 UTC · 6d agoAI safety & security1

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[hardware] Fullhan FH8626V100 - Multiple Vulnerabilities

Multiple vulnerabilities in the Fullhan FH8626V100 hardware chip have been disclosed alongside public proof-of-concept exploits.

Exploit-DB lists an entry covering multiple vulnerabilities in the Fullhan FH8626V100, a hardware component. The listing provides no CVE ids, vulnerability classes, or evidence of in-the-wild exploitation. Impact is likely limited to devices embedding the affected chip.

Exploit-DB·Sep 2, 00:00 UTC · 14d agoExploit / PoC

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VEX-Bench: Benchmarking LLM Agents for Assessing Exploitability of Software Supply Chain Vulnerabilities

Introduces VEX-Bench, 75 expert-labeled real-world cases testing whether LLM agents can assess supply chain vulnerability exploitability; frontier models reach about 80% F1.

VEX-Bench is the first benchmark evaluating LLM agents on assessing whether upstream dependency vulnerabilities are exploitable in downstream projects, with 75 real-world expert-labeled cases across Python, Java, and Go mined from GitHub. Nine models across three agent harnesses were evaluated; GPT-5.5 and Claude Opus 4.6 reach approximately 80% F1 on binary vulnerability-status classification, but only GPT-5.5 surpasses 70% macro-F1 on fine-grained justification classification. The gap highlights the difficulty of moving beyond binary exploitability calls to explaining exploitability reasons, unlike prior benchmarks targeting zero-day settings.

arXiv cs.CR·Sep 7, 22:52 UTC · 8d agoResearch1

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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.CR·Sep 3, 22:48 UTC · 12d agoResearch1

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[webapps] PodcastGenerator 3.2.9 - Stored XSS

A stored cross-site scripting flaw in PodcastGenerator 3.2.9 is documented with a public proof-of-concept exploit on Exploit-DB.

Exploit-DB published exploit ID 52677 targeting PodcastGenerator 3.2.9, a web application affected by stored cross-site scripting. The listing provides a proof-of-concept for the flaw but includes no CVE identifier or reports of active exploitation.

Exploit-DB·Sep 2, 00:00 UTC · 14d agoExploit / PoC1

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On Identifying Sound Conditions for Frontrunning Resistance

Researchers formally define smart-contract frontrunning resistance, showing 55% of 393 audited vulnerabilities escape state-of-the-art detection, and find two undisclosed Ethereum flaws.

The paper gives the first formal definition of frontrunning vulnerability for smart contracts, grounded in how honest users interact with contracts rather than contract code alone. In a large-scale study of 287 smart contract audits, 55% of the 393 vulnerabilities reported by leading auditors fall outside the scope of state-of-the-art dynamic detection criteria. The authors present a sound algorithm for synthesizing secure interaction conditions and apply it to real-world contracts, uncovering previously undiscovered vulnerabilities in two Ethereum contracts.

arXiv cs.CR·Sep 10, 13:35 UTC · 5d agoResearch

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When the prompt becomes the payload: A practical pen-testing guide for GenAI, LLM and RAG applications

CSO Online publishes a practical penetration-testing guide for GenAI, LLM, and RAG applications, covering prompt injection, retrieval poisoning, and tenant isolation testing.

The guide frames LLM applications as attack graphs spanning prompts, retrieval layers, vector stores, tools, identities, and downstream APIs, arguing that conventional web testing misses instruction-vs-data channel risks. It builds on OWASP prompt injection guidance (direct vs. indirect injection) and NIST's 2025 adversarial machine-learning taxonomy, noting that RAG and fine-tuning do not remove injection risk. Recommended practices include documenting trust transitions across components, using canaries and synthetic records to avoid test side effects, running multi-turn and obfuscated injection campaigns, and verifying chains from poisoned documents to observable state changes. It also details testing RAG pipelines via controlled document poisoning across metadata, OCR layers, and code comments, plus cross-tenant isolation checks on retrieved document IDs.

CSO Online·Sep 9, 10:00 UTC · 7d agoAI safety & security1

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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

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Can your coding style predict whether your code is vulnerable?

University of Massachusetts Dartmouth researchers present VulStyle, a stylometry-based vulnerability detector that also exposes benchmark reliability problems.

VulStyle combines stylometric features with syntax-tree structure and source tokens, pre-trained on about 4.9 million functions across seven programming languages and fine-tuned on five vulnerability detection datasets. It beat token-only detectors on some benchmarks but its F1 drops sharply on DiverseVul, which the authors link to noisy labels inflating reported performance across popular datasets. The authors argue style-aware detection should be harder to evade but did not test this empirically, and they note that uniform LLM-generated code may strip away the individual developer style the model depends on.

Help Net Security·Aug 24, 04:21 UTC · 23d agoResearch1

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Import AI 470: No rights for machines; automating environment generation with SPADE; and building better GPU kernels with Hawkeye

METR analysis finds AI accelerating cyber vulnerability discovery, while SPADE self-play environment generation improves Qwen3 reasoning benchmark scores at 30B scale.

Import AI 470 discusses a METR research note reporting differential acceleration from AI: major acceleration in reported cyber vulnerabilities (cURL, OpenSSL, Firefox, Microsoft, NVD, OSV), minor acceleration in mathematics, and no measurable acceleration in AI-research optimization benchmarks. It also covers SPADE, a self-play framework from a multi-university team (University of Washington, Stanford, MIT, CMU, and others) that co-evolves executable training environments and agent capability using Environment Designer and Reasoning Agent roles with hint-based regret rewards. Trained on Qwen3-4B-Instruct-2507, Qwen3-8B, and Qwen3-30B-A3B-Instruct-2507 via GRPO (400 rollouts of 25 environments), SPADE lifted the 30B-A3B game-environment suite average to 58.3, +8.1 over base, and improved tool-use results across backbones. The issue also references Hawkeye for building better GPU kernels.

Import AI·Aug 24, 13:12 UTC · 22d agoAI research

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Attackers Exploit Zimbra SNMP Flaw for Unauthenticated Remote Code Execution

CERT Polska and CISA report active exploitation of Zimbra RCE CVE-2026-73570, with 267 instances compromised per Shadowserver.

CVE-2026-73570 (CVSS 8.9) enables unauthenticated command injection and remote code execution in Zimbra Collaboration before 10.1.20 when the optional zimbra-snmp package is installed and SNMP notifications are enabled, via crafted SMTP requests. CISA added the flaw to its KEV catalog on August 21, 2026, with a federal patch deadline of August 24. The Shadowserver Foundation counted 267 compromised instances as of August 24, 2026, led by the US (46), Sweden (21), France (20) and Germany (17). Separately, Russia-linked Laundry Bear has weaponized Zimbra stored XSS CVE-2025-66376 against Western government and commercial mail servers since at least July 2025, delivering the ZimReaper payload.

The Hacker News·Aug 26, 05:08 UTC · 21d agoExploit / PoC in the wildCVE-2026-73570CVE-2025-663761

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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

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AI AppSec tools agree on just 5% of security findings

Contrast Security report finds 42 confirmed exploit attempts per application monthly and three AI scanners agreeing on only 5% of findings.

Contrast Security's AppSec Overflow 2026 report, drawing on telemetry from hundreds of thousands of production applications and APIs, found adversaries touch the average application every four minutes with 42 confirmed viable exploit attempts per application monthly, led by untrusted deserialization, path traversal, and method tampering. Legacy flaws Log4Shell and Spring4Shell remain widespread, mean time to exploit fell from over two years in 2018 to under three weeks for most 2025 exploited vulnerabilities, and average critical fix time is 92 days. Three AI scanners set on the same codebase agreed on only 5% of findings, and triaging a 2-million-line codebase scan cost roughly $128,000 versus $315 in API charges. Among exploited CVEs in the dataset, 82% of KEV-listed entries carried EPSS scores of 90% or higher, while CVE-2006-1547 and CVE-2023-38180 were confirmed exploited despite EPSS scores under 25%.

Help Net Security·Aug 31, 00:00 UTC · 16d agoResearch in the wildCVE-2006-1547CVE-2023-381801

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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

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Time Exploit Plummets Nday Flaws

Analysis shows time-to-exploit for n-day vulnerabilities has plummeted, shrinking defender patch windows as known flaws are exploited faster.

Infosecurity Magazine reports on analysis finding that the time between a vulnerability's disclosure and its exploitation in the wild has dropped sharply for n-day flaws. Faster exploitation compresses defenders' patching windows and raises the urgency of rapid patch deployment. The specific flaw families and metrics were not detailed in the available information.

Infosecurity Magazine·Aug 19, 00:00 UTC · 28d agoResearch in the wild

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AI Is Ending the Era of Hidden Vulnerabilities — Are Vendors Ready?

Dark Reading argues AI-assisted bug discovery is flooding vendors with vulnerability reports, straining disclosure processes and secure-by-design commitments.

The Dark Reading analysis describes a surge of bug reports driven by AI-powered discovery, exposing bottlenecks in vendor triage and disclosure pipelines. It argues this volume is revealing secure-by-design failures and questions whether vendors can keep pace with the rising tide of findings.

Dark Reading·Sep 4, 13:00 UTC · 12d agoIndustry

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An Empirical Analysis of ReDoS Vulnerabilities and ReDoS Detection Tools

Study of NVD data finds ReDoS vulnerabilities growing more prevalent and more likely to be exploited, while five detection tools disagree substantially.

The study compares five publicly available ReDoS detection tools and one regex correction tool across three datasets. An empirical analysis of all ReDoS vulnerabilities reported to the NVD finds they are becoming more prevalent and are much more likely to be exploited than non-ReDoS weaknesses. The detection tools exhibited substantial disagreement on whether a given regex is vulnerable.

arXiv cs.CR·Sep 9, 15:09 UTC · 6d agoResearch

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Automating Attack Graph Construction for Agentic Pentesting. Towards Neuro-Symbolic Vulnerability Hunting

Semi-automated pipeline converts Trivy, Semgrep, Nmap output into MulVAL attack graphs for agentic pentesting, 53.7% mean vulnerability coverage in CyBench.

The paper presents a semi-automated pipeline that parses Trivy, Semgrep, and Nmap findings into MulVAL predicates and uses an LLM-assisted process to build domain-specific Datalog rules linking scanner evidence to attack techniques. MulVAL/XSB then performs symbolic inference to generate structured, auditable attack paths for agentic pentesting. Evaluated on 54 web CTF tasks from CyBench, every task produced at least one goal-reaching graph with 53.7% mean ground-truth vulnerability coverage, 51.9% full coverage, and an 83.9% noise-path rate. Median end-to-end runtime was 24.9 seconds, making the pipeline runtime-practical for agentic workflows.

arXiv cs.CR·Sep 14, 13:13 UTC · 1d agoResearch

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