GHSA-RMRF-G9R3-73PM flagd Vulnerable to Allocation of Resources Without Limits or Throttling

Details flagd exposes OFREP /ofrep/v1/evaluate/... and gRPC evaluation.v1, evaluation.v2 endpoints for feature flag evaluation. These endpoints are designed to be publicly accessible by client applications. The evaluation context included in request payloads is read into memory without any size...

flagd Vulnerable to Allocation of Resources Without Limits or Throttling

Details flagd exposes OFREP /ofrep/v1/evaluate/... and gRPC evaluation.v1, evaluation.v2 endpoints for feature flag evaluation. These endpoints are designed to be publicly accessible by client applications. The evaluation context included in request payloads is read into memory without any size...

Allocation of Resources Without Limits or Throttling

Overview Affected versions of this package are vulnerable to Allocation of Resources Without Limits or Throttling via the evaluation endpoints, including /ofrep/v1/evaluate/flags/flagKey, /ofrep/v1/evaluate/flags, and various gRPC methods. An attacker can cause memory exhaustion and process...

TOSSS: A CVE-Based Software Security Benchmark for Large Language Models

With their increasing capabilities, Large Language Models LLMs are now used across many industries. They have become useful tools for software engineers and support a wide range of development tasks. As LLMs are increasingly used in software development workflows, a critical question arises: are...

OpenFeature flagd 安全漏洞

OpenFeature flagd is a daemon process developed by OpenFeature Corporation. Versions of flagd prior to 0.14.2 contained a security vulnerability. This vulnerability stemmed from the lack of size restrictions on the evaluation context in the request payload, which could lead to memory exhaustion a...

Adversarial Reinforcement Learning for Detecting False Data Injection Attacks in Vehicular Routing

In modern transportation networks, adversaries can manipulate routing algorithms using false data injection attacks, such as simulating heavy traffic with multiple devices running crowdsourced navigation applications, to mislead vehicles toward suboptimal routes and increase congestion. To addres...

VisualLeakBench: Auditing the Fragility of Large Vision-Language Models against PII Leakage and Social Engineering

As Large Vision-Language Models LVLMs are increasingly deployed in agent-integrated workflows and other deployment-relevant settings, their robustness against semantic visual attacks remains under-evaluated -- alignment is typically tested on explicit harmful content rather than privacy-critical...

Apeman Cameras

RISK EVALUATION Successful exploitation of these vulnerabilities could allow an attacker to take control of the device or view camera feeds. 2. RECOMMENDED PRACTICES CISA recommends users take defensive measures to minimize the risk of exploitation of these vulnerabilities, such as: Minimize...

Why LLMs Fail: A Failure Analysis and Partial Success Measurement for Automated Security Patch Generation

Large Language Models LLMs show promise for Automated Program Repair APR, yet their effectiveness on security vulnerabilities remains poorly characterized. This study analyzes 319 LLM-generated security patchesacross 64 Java vulnerabilities from the Vul4J benchmark. Using tri-axis evaluation...

Security Considerations for Multi-Agent Systems

Multi-agent artificial intelligence systems or MAS are systems of autonomous agents that exercise delegated tool authority, share persistent memory, and coordinate via inter-agent communication. MAS introduces qualitatively distinct security vulnerabilities from those documented for singular AI...

A Comparative Study of Recent Advances in Internet of Intrusion Detection Things

The Internet of Things IoT has revolutionized the way devices communicate and interact with each other, but it has also created new challenges in terms of security. In this context, intrusion detection has become a crucial mechanism to ensure the safety of IoT systems. To address this issue, a...

CVE-2026-29091

Locutus brings stdlibs of other programming languages to JavaScript for educational purposes. Prior to version 3.0.0, a remote code execution RCE flaw was discovered in the locutus project, specifically within the calluserfuncarray function implementation. The vulnerability allows an attacker to...

CVE-2026-29091 Locutus: Remote Code Execution (RCE) in locutus call_user_func_array due to Code Injection

Locutus brings stdlibs of other programming languages to JavaScript for educational purposes. Prior to version 3.0.0, a remote code execution RCE flaw was discovered in the locutus project, specifically within the calluserfuncarray function implementation. The vulnerability allows an attacker to...

SemFuzz: A Semantics-Aware Fuzzing Framework for Network Protocol Implementations

Network protocols are the foundation of modern communication, yet their implementations often contain semantic vulnerabilities stemming from inadequate understanding of specification semantics. Existing gray-box and black-box testing approaches lack semantic modeling of protocols, making it...

PQC-LEO: An Evaluation Framework for Post-Quantum Cryptographic Algorithms

Advances in quantum computing threaten digital communication security by undermining the foundations of current public-key cryptography through Shor's quantum algorithm. This has driven the development of Post-Quantum Cryptography PQC, a new set of algorithms resistant to quantum attacks. While...

Supporting Artifact Evaluation with LLMs: A Study with Published Security Research Papers

Artifact Evaluation AE is essential for ensuring the transparency and reliability of research, closing the gap between exploratory work and real-world deployment is particularly important in cybersecurity, particularly in IoT and CPSs, where large-scale, heterogeneous, and privacy-sensitive data...

SecureRAG-RTL: A Retrieval-Augmented, Multi-Agent, Zero-Shot LLM-Driven Framework for Hardware Vulnerability Detection

Large language models LLMs have shown remarkable capabilities in natural language processing tasks, yet their application in hardware security verification remains limited due to scarcity of publicly available hardware description language HDL datasets. This knowledge gap constrains LLM performan...

EVMbench: Evaluating AI Agents on Smart Contract Security

Smart contracts on public blockchains now manage large amounts of value, and vulnerabilities in these systems can lead to substantial losses. As AI agents become more capable at reading, writing, and running code, it is natural to ask how well they can already navigate this landscape, both in way...

New RFP Template for AI Usage Control and AI Governance 

As AI becomes the central engine for enterprise productivity, security leaders are finally getting the green light — and the budget — to secure it. But there’s a quiet crisis unfolding in the boardroom: many organizations know they need "AI Governance," but they have no idea what they are actuall...

Impact of 5G SA Logical Vulnerabilities on UAV Communications: Threat Models and Testbed Evaluation

This paper examines how logical vulnerabilities in 5G Standalone networks affect UAV command and control communication. The study looks at three attacker positions in the architecture: a malicious user equipment UE connected to the same logical network as the UAV, an attacker with access to the 5...