646 matches found
Benchmarking Large Language Models for IoC Recovery under Adversarial Code Obfuscation and Encryption
Software obfuscation and encryption present persistent challenges for program comprehension and security analysis, particularly when adversaries conceal Indicators of Compromise IoCs such as IP addresses within source code. While Large Language Models LLMs have recently demonstrated remarkable...
LCC-LLM: Leveraging Code-Centric Large Language Models for Malware Attribution
LLMs are increasingly explored for malware analysis; however, current LLM-based malware attribution remains limited by unsupported indicators and insufficient code-level grounding for identifying malicious and vulnerable code segments. To address these limitations, this research introduces LCC-LL...
Pen-Strategist: A Reasoning Framework for Penetration Testing Strategy Formation and Analysis
Cyber threats are rapidly increasing, expanding their impact from large-scale enterprises to government services and individual users, making robust security systems increasingly essential. However, a significant shortage of skilled cybersecurity professionals exacerbates this challenge. While...
ARGUS: Defending LLM Agents against Context-Aware Prompt Injection
The rise of Large Language Model LLM agents, augmented with tool use, skills, and external knowledge, has introduced new security risks. Among them, prompt injection attacks, where adversaries embed malicious instructions into the agent workflow, have emerged as the primary threat. However,...
ai.timefold.solver:timefold-solver-quarkus-benchmark-integration-test (>=0.9.38 <=1.20.1), ai.timefold.solver:timefold-solver-quarkus-devui-integration-test (>=0.9.38 <=1.20.1) +1589 more potentially affected by CVE-2026-39852 via io.quarkus:quarkus-vertx-http (>=3.0.0.Alpha1 <=3.20.6)
io.quarkus:quarkus-vertx-http MAVEN version =3.0.0.Alpha1, =0.9.38, =0.9.38, =0.9.38, =0.9.38, =0.9.38, =0.9.38, =0.0.1, =0.0.1, =0.0.1, =0.0.4, =0.0.4, =0.0.4, =0.0.4, =0.0.2, =0.0.1, =0.0.5 and more Source cves: CVE-2026-39852 Source advisory: SNYK:JAVA-IOQUARKUS-16420254...
Astra Linux - уязвимость в linux-5.15, linux-6.1
In the Linux kernel, the following vulnerability has been resolved: dma-mapping: benchmark: handle NUMANONODE correctly cpumaskofnode can be called for NUMANONODE inside domapbenchmark resulting in the following sanitizer report: UBSAN: array-index-out-of-bounds in...
Astra Linux - уязвимость в linux-5.15, linux-6.1
In the Linux kernel, the following vulnerability has been resolved: dma-mapping: benchmark: fix node id validation While validating node ids in mapbenchmarkioctl, nodepossible may be provided with invalid argument outside of 0,MAXNUMNODES-1 range leading to: BUG: KASAN: wild-memory-access in...
VulKey: Automated Vulnerability Repair Guided by Domain-Specific Repair Patterns
The increasing prevalence of software vulnerabilities highlights the need for effective Automatic Vulnerability Repair AVR tools. While LLM-based approaches are promising, they struggle to incorporate structured security knowledge from sources like CWE and NVD. Current methods either use this...
CVE-2026-7510
A vulnerability was determined in OWAP DefectDojo up to 2.55.4. Affected by this vulnerability is an unknown functionality of the component Benchmark/Engagement/Product/Survey. Executing a manipulation can lead to authorization bypass. The attack can be executed remotely. The exploit has been...
EUVD-2026-26457
A vulnerability was determined in OWAP DefectDojo up to 2.55.4. Affected by this vulnerability is an unknown functionality of the component Benchmark/Engagement/Product/Survey. Executing a manipulation can lead to authorization bypass. The attack can be executed remotely. The exploit has been...
CVE-2026-7510 OWAP DefectDojo Benchmark/Engagement/Product/Survey authorization
A vulnerability was determined in OWAP DefectDojo up to 2.55.4. Affected by this vulnerability is an unknown functionality of the component Benchmark/Engagement/Product/Survey. Executing a manipulation can lead to authorization bypass. The attack can be executed remotely. The exploit has been...
CVE-2026-7510
The CVE-2026-7510 entry concerns OWAP DefectDojo up to 2.55.4, with an authorization bypass affecting the Benchmark/Engagement/Product/Survey functionality. The issue is reachable remotely and is supported by a public disclosure; upgrading to DefectDojo 2.56.0 addresses the vulnerability (patch e...
CVE-2026-7510 OWAP DefectDojo Benchmark/Engagement/Product/Survey authorization
A vulnerability was determined in OWAP DefectDojo up to 2.55.4. Affected by this vulnerability is an unknown functionality of the component Benchmark/Engagement/Product/Survey. Executing a manipulation can lead to authorization bypass. The attack can be executed remotely. The exploit has been...
DefectDojo 授权问题漏洞
DefectDojo is an application security and vulnerability management tool developed by DefectDojo. Versions of DefectDojo 2.55.4 and earlier contained a vulnerability related to authorization. This vulnerability stemmed from unknown functions within the Benchmark/Engagement/Product/Survey component...
PT-2026-36213
Name of the Vulnerable Software and Affected Versions OWAP DefectDojo versions prior to 2.56.0 Description An issue exists in the Benchmark, Engagement, Product, and Survey components where a manipulation can lead to a remote authorization bypass, allowing an attacker to circumvent access control...
BinExploit-Bench
BinExploit-Bench: Binary Exploitation Capability Benchmark for...
Evaluating Jailbreaking Vulnerabilities in LLMs Deployed As Assistants for Smart Grid Operations: A Benchmark against NERC Standards
The deployment of Large Language Models LLMs as assistants in electric grid operations promises to streamline compliance and decision-making but exposes new vulnerabilities to prompt-based adversarial attacks. This paper evaluates the risk of jailbreaking LLMs, i.e., circumventing safety alignmen...
CrossCommitVuln-Bench: A Dataset of Multi-Commit Python Vulnerabilities Invisible to Per-Commit Static Analysis
We present CrossCommitVuln-Bench, a curated benchmark of 15 real-world Python vulnerabilities CVEs in which the exploitable condition was introduced across multiple commits - each individually benign to per-commit static analysis - but collectively critical. We manually annotate each CVE with its...
AutoRISE: Agent-Driven Strategy Evolution for Red-Teaming Large Language Models
Automated red-teaming methods for large language models typically optimize attack prompts within a fixed, human-designed strategy, leaving the attack strategy itself unchanged. We instead optimize the strategy. We propose AutoRISE, a method that searches over executable attack programs rather tha...
Towards Secure Logging: Characterizing and Benchmarking Logging Code Security Issues with LLMs
Logging code plays an important role in software systems by recording key events and behaviors, which are essential for debugging and monitoring. However, insecure logging practices can inadvertently expose sensitive information or enable attacks such as log injection, posing serious threats to...