expat: libexpat: Denial of Service due to incorrect Unicode surrogate handling

A flaw in libexpat's toUtf16 functions mishandles Unicode low surrogates by treating them as high surrogates. An attacker can exploit the resulting out-of-bounds read to trigger an infinite loop, causing a denial of service DoS...

[slackware-security] expat

New expat packages are available for Slackware 15.0 and -current to fix a security issue. Here are the details from the Slackware 15.0 ChangeLog: patches/packages/expat-2.7.5-i586-3slack15.0.txz: Rebuilt. This update fixes a security issue: Fix an out-of-bounds read and the resulting infinite loo...

CVE-2026-72522

A flaw in libexpat's toUtf16 functions mishandles Unicode low surrogates by treating them as high surrogates. An attacker can exploit the resulting out-of-bounds read to trigger an infinite loop, causing a denial of service DoS. Mitigation Limit exposure by restricting the parsing of untrusted or...

CVE-2026-72522

libexpat before 2.8.3 has an out-of-bounds read and resultant infinite loop because low surrogates are treated the same as high surrogates during Unicode processing in the toUtf16 functions...

EUVD-2026-54990

libexpat before 2.8.3 has an out-of-bounds read and resultant infinite loop because low surrogates are treated the same as high surrogates during Unicode processing in the toUtf16 functions...

CVE-2026-72522

libexpat before 2.8.3 has an out-of-bounds read and resultant infinite loop because low surrogates are treated the same as high surrogates during Unicode processing in the toUtf16 functions...

CVE-2026-72522

libexpat before 2.8.3 has an out-of-bounds read and resultant infinite loop because low surrogates are treated the same as high surrogates during Unicode processing in the toUtf16 functions...

PYSEC-2026-1057 Incorrect handling of invalid surrogate pair characters

Impact What kind of vulnerability is it? Who is impacted? Anyone parsing JSON from an untrusted source is vulnerable. JSON strings that contain escaped surrogate characters not part of a proper surrogate pair were decoded incorrectly. Besides corrupting strings, this allowed for potential key...

Astra Linux – Vulnerability in ujson

UltraJSON is a fast JSON encoder and decoder written in pure C, with bindings for Python 3.7+. It was found that affected versions incorrectly decoded certain characters. JSON strings containing escaped surrogate characters that were not part of a valid surrogate pair were decoded incorrectly. Th...

Formulating Subgroup Discovery As a Quantum Optimization Problem for Network Security

While current network intrusion detection systems achieve satisfactory accuracy, they often lack explainability. Subgroup Discovery SD addresses this by building interpretable rules that characterize feature interactions associated with attack traffic. With large datasets, classical heuristic bea...

ExAI5G: A Logic-Based Explainable AI Framework for Intrusion Detection in 5G Networks

Intrusion detection systems IDSs for 5G networks must handle complex, high-volume traffic. Although opaque "black-box" models can achieve high accuracy, their lack of transparency hinders trust and effective operational response. We propose ExAI5G, a framework that prioritizes interpretability by...

Not All Tokens Are Created Equal: Query-Efficient Jailbreak Fuzzing for LLMs

Large Language ModelsLLMs are widely deployed, yet are vulnerable to jailbreak prompts that elicit policy-violating outputs. Although prior studies have uncovered these risks, they typically treat all tokens as equally important during prompt mutation, overlooking the varying contributions of...

The Role of Learning in Attacking Intrusion Detection Systems

Recent work on network attacks have demonstrated that ML-based network intrusion detection systems NIDS can be evaded with adversarial perturbations. However, these attacks rely on complex optimizations that have large computational overheads, making them impractical in many real-world settings. ...

FedPoisonTTP: A Threat Model and Poisoning Attack for Federated Test-Time Personalization

Test-time personalization in federated learning enables models at clients to adjust online to local domain shifts, enhancing robustness and personalization in deployment. Yet, existing federated learning work largely overlooks the security risks that arise when local adaptation occurs at test tim...

BackWeak: Backdooring Knowledge Distillation Simply with Weak Triggers and Fine-Tuning

Knowledge Distillation KD is essential for compressing large models, yet relying on pre-trained "teacher" models downloaded from third-party repositories introduces serious security risks -- most notably backdoor attacks. Existing KD backdoor methods are typically complex and computationally...

Quantifying the Risk of Transferred Black Box Attacks

Neural networks have become pervasive across various applications, including security-related products. However, their widespread adoption has heightened concerns regarding vulnerability to adversarial attacks. With emerging regulations and standards emphasizing security, organizations must...

Black-Box Guardrail Reverse-Engineering Attack

Large language models LLMs increasingly employ guardrails to enforce ethical, legal, and application-specific constraints on their outputs. While effective at mitigating harmful responses, these guardrails introduce a new class of vulnerabilities by exposing observable decision patterns. In this...

EUVD-2022-6438

Malicious code in bioql PyPI...

EUVD-2021-27532

Malicious code in bioql PyPI...

Learning-Based Privacy-Preserving Graph Publishing against Sensitive Link Inference Attacks

Publishing graph data is widely desired to enable a variety of structural analyses and downstream tasks. However, it also potentially poses severe privacy leakage, as attackers may leverage the released graph data to launch attacks and precisely infer private information such as the existence of...