Context-Aware Web Attack Detection in Open-Source SIEM Systems Via MITRE ATT&CK-Enriched Behavioral Profiling

Security Information and Event Management SIEM systems aggregate log data from heterogeneous sources to detect coordinated attacks. Traditional rule-based correlation engines struggle to classify multi-step web application attacks because they examine each event without reference to the behaviour...

Gray-Box Poisoning of Continuous Malware Ingestion Pipelines

Modern malware detection pipelines rely on continuous data ingestion and machine learning to counter the high volume of novel threats. This work investigates a realistic gray-box poisoning threat model targeting these pipelines. Using the secmlmalware framework, we generate problem-space...

harfbuzz:hb-gpu-fuzzer: Segv on unknown address in hb_font_get_scale

Project: https://github.com/harfbuzz/harfbuzz.git Detailed Report: https://oss-fuzz.com/testcase?key=6573156621156352 Project: harfbuzz Fuzzing Engine: afl Fuzz Target: hb-gpu-fuzzer Job Type: aflasanharfbuzz Platform Id: linux Crash Type: Segv on unknown address Crash Address: Crash State:...

RansomTrack: A Hybrid Behavioral Analysis Framework for Ransomware Detection

Ransomware poses a serious and fast-acting threat to critical systems, often encrypting files within seconds of execution. Research indicates that ransomware is the most reported cybercrime in terms of financial damage, highlighting the urgent need for early-stage detection before encryption is...

harfbuzz:hb-raster-fuzzer: Crash in hb_raster_paint_radial_gradient

Project: https://github.com/harfbuzz/harfbuzz.git Detailed Report: https://oss-fuzz.com/testcase?key=6597066439852032 Project: harfbuzz Fuzzing Engine: afl Fuzz Target: hb-raster-fuzzer Job Type: aflasanharfbuzz Platform Id: linux Crash Type: UNKNOWN READ Crash Address: 0x767ea1e57920 Crash State...

GMA-SAWGAN-GP: A Novel Data Generative Framework to Enhance IDS Detection Performance

Intrusion Detection System IDS is often calibrated to known attacks and generalizes poorly to unknown threats. This paper proposes GMA-SAWGAN-GP, a novel generative augmentation framework built on a Self-Attention-enhanced Wasserstein GAN with Gradient Penalty WGAN-GP. The generator employs...

A Novel Solution for Zero-Day Attack Detection in IDS Using Self-Attention and Jensen-Shannon Divergence in WGAN-GP

The increasing sophistication of cyber threats, especially zero-day attacks, poses a significant challenge to cybersecurity. Zero-day attacks exploit unknown vulnerabilities, making them difficult to detect and defend against. Existing approaches patch flaws and deploy an Intrusion Detection Syst...

harfbuzz:hb-raster-fuzzer: Stack-buffer-underflow in evaluate_color_line

Project: https://github.com/harfbuzz/harfbuzz.git Detailed Report: https://oss-fuzz.com/testcase?key=4635834988167168 Project: harfbuzz Fuzzing Engine: libFuzzer Fuzz Target: hb-raster-fuzzer Job Type: libfuzzerasani386harfbuzz Platform Id: linux Crash Type: Stack-buffer-underflow READ 4 Crash...

PT-2026-25643

An out-of-bounds read vulnerability exists in the EMF functionality of Canva Affinity. By using a specially crafted EMF file, an attacker could exploit this vulnerability to perform an out-of-bounds read, potentially leading to the disclosure of sensitive information...

PT-2026-25642

An out-of-bounds read vulnerability exists in the EMF functionality of Canva Affinity. By using a specially crafted EMF file, an attacker could exploit this vulnerability to perform an out-of-bounds read, potentially leading to the disclosure of sensitive information...

PT-2026-25650

An out-of-bounds read vulnerability exists in the EMF functionality of Canva Affinity. By using a specially crafted EMF file, an attacker could exploit this vulnerability to perform an out-of-bounds read, potentially leading to the disclosure of sensitive information...

PT-2026-25647

An out‑of‑bounds write vulnerability exists in the EMF functionality of Canva Affinity. By using a specially crafted EMF file, an attacker could exploit this vulnerability to perform an out‑of‑bounds write, potentially leading to code execution...

PT-2026-25656

An out-of-bounds read vulnerability exists in the EMF functionality of Canva Affinity. By using a specially crafted EMF file, an attacker could exploit this vulnerability to perform an out-of-bounds read, potentially leading to the disclosure of sensitive information...

harfbuzz:hb-raster-fuzzer: Crash in evaluate_color_line

Project: https://github.com/harfbuzz/harfbuzz.git Detailed Report: https://oss-fuzz.com/testcase?key=5216672087867392 Project: harfbuzz Fuzzing Engine: honggfuzz Fuzz Target: hb-raster-fuzzer Job Type: honggfuzzasanharfbuzz Platform Id: linux Crash Type: UNKNOWN READ Crash Address: 0x7ab9d62d4814...

Enhancing Network Intrusion Detection Systems: A Multi-Layer Ensemble Approach to Mitigate Adversarial Attacks

Adversarial examples can represent a serious threat to machine learning ML algorithms. If used to manipulate the behaviour of ML-based Network Intrusion Detection Systems NIDS, they can jeopardize network security. In this work, we aim to mitigate such risks by increasing the robustness of NIDS...

GoodVibe: Security-By-Vibe for LLM-Based Code Generation

Large language models LLMs are increasingly used for code generation in fast, informal development workflows, often referred to as vibe coding, where speed and convenience are prioritized, and security requirements are rarely made explicit. In this setting, models frequently produce functionally...

When Handshakes Tell the Truth: Detecting Web Bad Bots Via TLS Fingerprints

Automated traffic continued to surpass human-generated traffic on the web, and a rising proportion of this automation was explicitly malicious. Evasive bots could pretend to be real users, even solve Captchas and mimic human interaction patterns. This work explores a less intrusive, protocol-leve...

Malware Detection through Memory Analysis

This paper summarizes the research conducted for a malware detection project using the Canadian Institute for Cybersecurity's MalMemAnalysis-2022 dataset. The purpose of the project was to explore the effectiveness and efficiency of machine learning techniques for the task of binary classificatio...

Jailbreaking LLMs Via Calibration

Safety alignment in Large Language Models LLMs often creates a systematic discrepancy between a model's aligned output and the underlying pre-aligned data distribution. We propose a framework in which the effect of safety alignment on next-token prediction is modeled as a systematic distortion of...

Explainability Methods for Hardware Trojan Detection: A Systematic Comparison

Hardware trojan detection requires accurate identification and interpretable explanations for security engineers to validate and act on results. This work compares three explainability categories for gate-level trojan detection on the Trust-Hub benchmark: 1 domain-aware property-based analysis of...