CVE-2025-49847 llama.cpp Vulnerable to Buffer Overflow via Malicious GGUF Model

llama.cpp is an inference of several LLM models in C/C++. Prior to version b5662, an attacker‐supplied GGUF model vocabulary can trigger a buffer overflow in llama.cpp’s vocabulary‐loading code. Specifically, the helper trycopy in llama.cpp/src/vocab.cpp: llamavocab::impl::tokentopiece casts a ve...

CVE-2025-49847 llama.cpp Vulnerable to Buffer Overflow via Malicious GGUF Model

llama.cpp is an inference of several LLM models in C/C++. Prior to version b5662, an attacker‐supplied GGUF model vocabulary can trigger a buffer overflow in llama.cpp’s vocabulary‐loading code. Specifically, the helper trycopy in llama.cpp/src/vocab.cpp: llamavocab::impl::tokentopiece casts a ve...

CVE-2025-49847 llama.cpp Vulnerable to Buffer Overflow via Malicious GGUF Model

llama.cpp is an inference of several LLM models in C/C++. Prior to version b5662, an attacker‐supplied GGUF model vocabulary can trigger a buffer overflow in llama.cpp’s vocabulary‐loading code. Specifically, the helper trycopy in llama.cpp/src/vocab.cpp: llamavocab::impl::tokentopiece casts a ve...

PT-2025-25757 · Llama.Cpp · Llama.Cpp

Name of the Vulnerable Software and Affected Versions: llama.cpp versions prior to b5662 Description: The issue is related to a buffer overflow in the vocabulary-loading code of llama.cpp. An attacker-supplied GGUF model vocabulary can trigger this overflow. Specifically, the helper function toke...

LLM Jailbreak Oracle

As large language models LLMs become increasingly deployed in safety-critical applications, the lack of systematic methods to assess their vulnerability to jailbreak attacks presents a critical security gap. We introduce the jailbreak oracle problem: given a model, prompt, and decoding strategy,...

Astra Linux – Vulnerability found in Linux 6.1, Linux 6.12

In the Linux kernel, the following vulnerability has been resolved: x86/amdnb: The function amdgetmmconfigrange uses rdmsrsafe, which should not be used without proper safeguards. Xen does not provide the MSRFAM10HMMIOCONFbase to all guests. This results in the following warning: Unchecked MSR...

Playbook: Transforming Your Cybersecurity Practice Into An MRR Machine

Introduction The cybersecurity landscape is evolving rapidly, and so are the cyber needs of organizations worldwide. While businesses face mounting pressure from regulators, insurers, and rising threats, many still treat cybersecurity as an afterthought. As a result, providers may struggle to mov...

TencentOS Server 4: nodejs20 (TSSA-2025:0293)

The version of Tencent Linux installed on the remote TencentOS Server 4 host is prior to tested version. It is, therefore, affected by multiple vulnerabilities as referenced in the TSSA-2025:0293 advisory. Package updates are available for TencentOS Server 4 that fix the following vulnerabilities...

CVE-2025-45988

Blink routers BL-WR9000 V2.4.9 , BL-AC2100AZ3 V1.0.4, BL-X10AC8 v1.0.5 , BL-LTE300 v1.2.3, BL-F1200AT1 v1.0.0, BL-X26AC8 v1.2.8, BLAC450MAE4 v4.0.0 and BL-X26DA3 v1.2.7 were discovered to contain multiple command injection vulnerabilities via the cmd parameter in the bsSetCmd function...

I Know What You Said: Unveiling Hardware Cache Side-Channels in Local Large Language Model Inference

Large Language Models LLMs that can be deployed locally have recently gained popularity for privacy-sensitive tasks, with companies such as Meta, Google, and Intel playing significant roles in their development. However, the security of local LLMs through the lens of hardware cache side-channels...

Exploit for Integer Overflow or Wraparound in Tesla Model_3_Firmware

Tesla Nasıl Hacklenir? — Etkileşimli Senaryo Uygulaması Bu pr...

Exploit for CVE-2025-52357

CVE-2025-52357 : Security Advisory: XSS in FD602GW-DX-R410 Rou...

New TokenBreak Attack Bypasses AI Moderation with Single-Character Text Changes

Cybersecurity researchers have discovered a novel attack technique called TokenBreak that can be used to bypass a large language model's LLM safety and content moderation guardrails with just a single character change. "The TokenBreak attack targets a text classification model's tokenization...

Uncovering Reliable Indicators: Improving IoC Extraction from Threat Reports

Indicators of Compromise IoCs are critical for threat detection and response, marking malicious activity across networks and systems. Yet, the effectiveness of automated IoC extraction systems is fundamentally limited by one key issue: the lack of high-quality ground truth. Current extraction too...

SOFT: Selective Data Obfuscation for Protecting LLM Fine-Tuning against Membership Inference Attacks

Whitepaper called SOFT: Selective Data Obfuscation For Protecting LLM Fine-Tuning Against Membership Inference Attacks...

ObfusBFA: a Holistic Approach to Safeguarding DNNs from Different Types of Bit-Flip Attacks

Bit-flip attacks BFAs represent a serious threat to Deep Neural Networks DNNs, where flipping a small number of bits in the model parameters or binary code can significantly degrade the model accuracy or mislead the model prediction in a desired way. Existing defenses exclusively focus on...

MAYA: Addressing Inconsistencies in Generative Password Guessing through a Unified Benchmark

Recent advances in generative models have led to their application in password guessing, with the aim of replicating the complexity, structure, and patterns of human-created passwords. Despite their potential, inconsistencies and inadequate evaluation methodologies in prior research have hindered...

CVE-2025-31052

Deserialization of Untrusted Data vulnerability in themeton The Fashion - Model Agency One Page Beauty Theme nrgfashion allows Object Injection.This issue affects The Fashion - Model Agency One Page Beauty Theme: from n/a through = 1.4.4...

How to Build a Lean Security Model: 5 Lessons from River Island

In today’s security landscape, budgets are tight, attack surfaces are sprawling, and new threats emerge daily. Maintaining a strong security posture under these circumstances without a large team or budget can be a real challenge. Yet lean security models are not only possible - they can be highl...

LLMail-Inject: a Dataset from a Realistic Adaptive Prompt Injection Challenge

Indirect Prompt Injection attacks exploit the inherent limitation of Large Language Models LLMs to distinguish between instructions and data in their inputs. Despite numerous defense proposals, the systematic evaluation against adaptive adversaries remains limited, even when successful attacks ca...