CVE-2024-49820

IBM Security Guardium Key Lifecycle Manager 4.1, 4.1.1, 4.2.0, and 4.2.1 could allow a remote attacker to obtain sensitive information, caused by the failure to properly enable HTTP Strict Transport Security. An attacker could exploit this vulnerability to obtain sensitive information using man i...

CVE-2023-31004

IBM Security Access Manager Container IBM Security Verify Access Appliance 10.0.0.0 through 10.0.6.1 and IBM Security Verify Access Docker 10.0.0.0 through 10.0.6.1 could allow a remote attacker to gain access to the underlying system using man in the middle techniques. IBM X-Force ID: 254765...

CVE-2023-22863

IBM Robotic Process Automation 20.12.0 through 21.0.2 defaults to HTTP in some RPA commands when the prefix is not explicitly specified in the URL. This could allow an attacker to obtain sensitive information using man in the middle techniques. IBM X-Force ID: 244109...

CVE-2023-3768

Incorrect data input validation vulnerability, which could allow an attacker with access to the network to implement fuzzing techniques that would allow him to gain knowledge about specially crafted packets that would create a DoS condition through the MMS protocol when initiating communication,...

CVE-2023-6746

An insertion of sensitive information into log file vulnerability was identified in the log files for a GitHub Enterprise Server back-end service that could permit an adversary in the middle attack when combined with other phishing techniques. To exploit this, an attacker would need access to the...

Lumma Stealer: Breaking down the delivery techniques and capabilities of a prolific infostealer

Over the past year, Microsoft observed the persistent growth and operational sophistication of Lumma Stealer, an infostealer malware used by multiple financially motivated threat actors to target various industries. Our investigation into Lumma Stealer’s distribution infrastructure reveals a...

Bypass SharePoint Restricted View to exfiltrate data using Copilot AI and more…

TL;DR Restricted View allows users to read files, but not copy, download or print them Attackers will look for ways to circumvent these controls Traditional workarounds include manual transcription, screenshots, and photos OCR tools can extract text from screenshots Microsoft Copilot can read fil...

PsyScam: a Benchmark for Psychological Techniques in Real-World Scams

Online scams have become increasingly prevalent, with scammers using psychological techniques PTs to manipulate victims. While existing research has developed benchmarks to study scammer behaviors, these benchmarks do not adequately reflect the PTs observed in real-world scams. To fill this gap, ...

R1dacted: Investigating Local Censorship in DeepSeek'S R1 Language Model

DeepSeek recently released R1, a high-performing large language model LLM optimized for reasoning tasks. Despite its efficient training pipeline, R1 achieves competitive performance, even surpassing leading reasoning models like OpenAI's o1 on several benchmarks. However, emerging reports suggest...

TechniqueRAG: Retrieval Augmented Generation for Adversarial Technique Annotation in Cyber Threat Intelligence Text

Accurately identifying adversarial techniques in security texts is critical for effective cyber defense. However, existing methods face a fundamental trade-off: they either rely on generic models with limited domain precision or require resource-intensive pipelines that depend on large labeled...

Server-Side Template Injection Vulnerabilities and Exploitation Techniques

Research article called Server-Side Template Injection SSTI Vulnerabilities and Exploitation Techniques. The paper provides a structured methodology for detecting and exploiting SSTI vulnerabilities across multiple template engines, along with real-world case studies and mitigation strategies...

Understanding and Characterizing Obfuscated Funds Transfers in Ethereum Smart Contracts

Scam contracts on Ethereum have rapidly evolved alongside the rise of DeFi and NFT ecosystems, utilizing increasingly complex code obfuscation techniques to avoid early detection. This paper systematically investigates how obfuscation amplifies the financial risks of fraudulent contracts and...

On Technique Identification and Threat-Actor Attribution Using LLMs and Embedding Models

Attribution of cyber-attacks remains a complex but critical challenge for cyber defenders. Currently, manual extraction of behavioral indicators from dense forensic documentation causes significant attribution delays, especially following major incidents at the international scale. This research...

Private Transformer Inference in MLaaS: a Survey

Transformer models have revolutionized AI, powering applications like content generation and sentiment analysis. However, their deployment in Machine Learning as a Service MLaaS raises significant privacy concerns, primarily due to the centralized processing of sensitive user data. Private...

SecReEvalBench: a Multi-Turned Security Resilience Evaluation Benchmark for Large Language Models

The increasing deployment of large language models in security-sensitive domains necessitates rigorous evaluation of their resilience against adversarial prompt-based attacks. While previous benchmarks have focused on security evaluations with limited and predefined attack domains, such as...

Privacy-Preserving Runtime Verification

Runtime verification offers scalable solutions to improve the safety and reliability of systems. However, systems that require verification or monitoring by a third party to ensure compliance with a specification might contain sensitive information, causing privacy concerns when usual runtime...

MUBox: a Critical Evaluation Framework of Deep Machine Unlearning

Recent legal frameworks have mandated the right to be forgotten, obligating the removal of specific data upon user requests. Machine Unlearning has emerged as a promising solution by selectively removing learned information from machine learning models. This paper presents MUBox, a comprehensive...

Fair Play for Individuals, Foul Play for Groups? Auditing Anonymization'S Impact on ML Fairness

Machine learning ML algorithms are heavily based on the availability of training data, which, depending on the domain, often includes sensitive information about data providers. This raises critical privacy concerns. Anonymization techniques have emerged as a practical solution to address these...

LM-Scout: Analyzing the Security of Language Model Integration in Android Apps

Developers are increasingly integrating Language Models LMs into their mobile apps to provide features such as chat-based assistants. To prevent LM misuse, they impose various restrictions, including limits on the number of queries, input length, and allowed topics. However, if the LM integration...

38,000+ FreeDrain Subdomains Found Exploiting SEO to Steal Crypto Wallet Seed Phrases

Cybersecurity researchers have exposed what they say is an "industrial-scale, global cryptocurrency phishing operation" engineered to steal digital assets from cryptocurrency wallets for several years. The campaign has been codenamed FreeDrain by threat intelligence firms SentinelOne and Validin...