Intermittent File Encryption in Ransomware: Measurement, Modeling, and Detection

File encrypting ransomware increasingly employs intermittent encryption techniques, encrypting only parts of files to evade classical detection methods. These strategies, exemplified by ransomware families like BlackCat, complicate file structure based detection techniques due to diverse file...

PoTS: Proof-Of-Training-Steps for Backdoor Detection in Large Language Models

As Large Language Models LLMs gain traction across critical domains, ensuring secure and trustworthy training processes has become a major concern. Backdoor attacks, where malicious actors inject hidden triggers into training data, are particularly insidious and difficult to detect. Existing...

Leveraging Code Cohesion Analysis to Identify Source Code Supply Chain Attacks

Supply chain attacks significantly threaten software security with malicious code injections within legitimate projects. Such attacks are very rare but may have a devastating impact. Detecting spurious code injections using automated tools is further complicated as it often requires deciphering t...

Beyond a Single Perspective: Towards a Realistic Evaluation of Website Fingerprinting Attacks

Website Fingerprinting WF attacks exploit patterns in encrypted traffic to infer the websites visited by users, posing a serious threat to anonymous communication systems. Although recent WF techniques achieve over 90% accuracy in controlled experimental settings, most studies remain confined to...

A Novel GPT-Based Framework for Anomaly Detection in System Logs

Identification of anomalous events within system logs constitutes a pivotal element within the frame- work of cybersecurity defense strategies. However, this process faces numerous challenges, including the management of substantial data volumes, the distribution of anomalies, and the precision o...

A Hard-Label Black-Box Evasion Attack against ML-Based Malicious Traffic Detection Systems

Machine Learning ML-based malicious traffic detection is a promising security paradigm. It outperforms rule-based traditional detection by identifying various advanced attacks. However, the robustness of these ML models is largely unexplored, thereby allowing attackers to craft adversarial traffi...

Rapid7: 7 years of recognition in Gartner® Magic Quadrant™ for SIEM

We’re proud to share that Rapid7 has been recognized in the 2025 Gartner Magic Quadrant for Security Information and Event Management SIEM. This is the seventh year we have been positioned in this report, which means we’ve been recognized in every report following the launch of our SIEM offering,...

Multiple Cisco Products Snort 3 MIME Denial of Service Vulnerabilities

Multiple Cisco products are affected by vulnerabilities in the HTTP Multipurpose Internet Mail Extensions MIME Decoder that could allow an unauthenticated, remote attacker to cause the Snort 3 Detection Engine to leak possible sensitive information or to restart. For more information about these...

aether

Aether - Adaptive Exploit & Threat Hunting Engine for EVM-base...

Quarterly WordPress Threat Intelligence Report – Q3 2025

As the leader in WordPress security, Wordfence provides unparalleled security coverage that fully encompasses protection, active monitoring, detection, and response all built around our threat intelligence, demonstrating a strong commitment to security. Our mission is to ensure comprehensive...

Infrastructure Patterns in Toll Scam Domains: A Comprehensive Analysis of Cybercriminal Registration and Hosting Strategies

Toll scams involve criminals registering fake domains that pretend to be legitimate transportation agencies to trick users into making fraudulent payments. Although these scams are rapidly increasing and causing significant harm, they have not been extensively studied. We present the first...

The Silent Threat in Active Directory: How AS-REP Roasting Steals Passwords Without a Trace and Trellix NDR’s Rapid Detection

The Silent Threat in Active Directory: How AS-REP Roasting Steals Passwords Without a Trace and Trellix NDR’s Rapid Detection By Maulik Maheta · October 15, 2025 Executive summary Adversaries use AS-REP Roasting to extract and crack password hashes from Active Directory AD accounts with Kerberos...

GRIDAI: Generating and Repairing Intrusion Detection Rules Via Collaboration among Multiple LLM-Based Agents

Rule-based network intrusion detection systems play a crucial role in the real-time detection of Web attacks. However, most existing works primarily focus on automatically generating detection rules for new attacks, often overlooking the relationships between new attacks and existing rules, which...

Multiple Cisco Products Snort 3 MIME DoS Vulnerabilities (cisco-sa-snort3-mime-vulns-tTL8PgVH_CVE-2025-20360)

According to its self-reported version, Cisco ASA Software is affected by a vulnerability. - Multiple Cisco products are affected by a vulnerability in the Snort 3 HTTP Decoder that could allow an unauthenticated, remote attacker to cause the Snort 3 Detection Engine to restart. This vulnerabilit...

EUVD-2022-55137

In the Linux kernel, the following vulnerability has been resolved: powerpc: Fix virtaddrvalid for 64-bit Book3E & 32-bit mpe: On 64-bit Book3E vmalloc space starts at 0x8000000000000000. Because of the way pa works we have: pa0x8000000000000000 == 0, and therefore virttopfn0x8000000000000000 == ...

org.springframework/spring-core: Spring Framework Annotation Detection Vulnerability

The Spring Framework annotation detection mechanism may not correctly resolve annotations on methods within type hierarchies with a parameterized super type with unbounded generics. This can be an issue if such annotations are used for authorization decisions...

CVE-2025-59243

creationtimestamp| type| source ---|---|--- 2025-10-14 16:38:05+00:00| seen| https://advisories.ncsc.nl/advisory?id=NCSC-2025-0315 2025-10-14 16:38:44+00:00| seen| https://www.thezdi.com/blog/2025/10/14/the-october-2025-security-update-review 2025-10-14 17:23:28+00:00| seen|...

CVE-2025-55078

creationtimestamp| type| source ---|---|--- 2025-10-14 09:34:05+00:00| seen| https://bsky.app/profile/basefortify.bsky.social/post/3m35ges75m22h...

Dell Enterprise SONiC OS Detection

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DeepTrust: Multi-Step Classification through Dissimilar Adversarial Representations for Robust Android Malware Detection

Over the last decade, machine learning has been extensively applied to identify malicious Android applications. However, such approaches remain vulnerable against adversarial examples, i.e., examples that are subtly manipulated to fool a machine learning model into making incorrect predictions...