UBUNTU-CVE-2025-5878

A vulnerability was found in ESAPI esapi-java-legacy and classified as problematic. This issue affects the interface Encoder.encodeForSQL of the SQL Injection Defense. An attack leads to an improper neutralization of special elements. The attack may be initiated remotely and an exploit has been...

CVE-2025-5878 ESAPI esapi-java-legacy SQL Injection Defense Encoder.encodeForSQL special element

A vulnerability was found in ESAPI esapi-java-legacy and classified as problematic. This issue affects the interface Encoder.encodeForSQL of the SQL Injection Defense. An attack leads to an improper neutralization of special elements. The attack may be initiated remotely and an exploit has been...

PT-2025-27359

Name of the Vulnerable Software and Affected Versions: ESAPI esapi-java-legacy versions prior to 2.7.0.0 Description: A vulnerability was found in the interface Encoder.encodeForSQL of the SQL Injection Defense, leading to an improper neutralization of special elements. The attack may be initiate...

Advancing Jailbreak Strategies: a Hybrid Approach to Exploiting LLM Vulnerabilities and Bypassing Modern Defenses

The advancement of Pre-Trained Language Models PTLMs and Large Language Models LLMs has led to their widespread adoption across diverse applications. Despite their success, these models remain vulnerable to attacks that exploit their inherent weaknesses to bypass safety measures. Two primary...

CVE-2025-52904 File Browser: Command Execution not Limited to Scope

File Browser provides a file managing interface within a specified directory and it can be used to upload, delete, preview, rename and edit files. In versions of the web application on the 2.x branch, all users have a scope assigned, and they only have access to the files within that scope. The...

Parsons AccuWeather widget

RISK EVALUATION Successful exploitation of this vulnerability could allow an attacker to insert a malicious link that users might access through the RSS feed. 2. RECOMMENDED PRACTICES CISA recommends users take defensive measures to minimize the risk of exploitation of this vulnerability, such...

ControlID iDSecure On-premises

RISK EVALUATION Successful exploitation of these vulnerabilities could allow an attacker to bypass authentication, retrieve information, leak arbitrary data, or perform SQL injections. 2. RECOMMENDED PRACTICES CISA recommends users take defensive measures to minimize the risk of exploitation of...

Retrieval-Confused Generation Is a Good Defender for Privacy Violation Attack of Large Language Models

Recent advances in large language models LLMs have made a profound impact on our society and also raised new security concerns. Particularly, due to the remarkable inference ability of LLMs, the privacy violation attack PVA, revealed by Staab et al., introduces serious personal privacy issues...

A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures

In recent years, Large-Language-Model-driven AI agents have exhibited unprecedented intelligence, flexibility, and adaptability, and are rapidly changing human production and lifestyle. Nowadays, agents are undergoing a new round of evolution. They no longer act as an isolated island like LLMs...

Automatic Selection of Protections to Mitigate Risks against Software Applications

This paper introduces a novel approach for the automated selection of software protections to mitigate MATE risks against critical assets within software applications. We formalize the key elements involved in protection decision-making - including code artifacts, assets, security requirements,...

InfoFlood: Jailbreaking Large Language Models with Information Overload

Large Language Models LLMs have demonstrated remarkable capabilities across various domains. However, their potential to generate harmful responses has raised significant societal and regulatory concerns, especially when manipulated by adversarial techniques known as "jailbreak" attacks. Existing...

InverTune: Removing Backdoors from Multimodal Contrastive Learning Models Via Trigger Inversion and Activation Tuning

Multimodal contrastive learning models like CLIP have demonstrated remarkable vision-language alignment capabilities, yet their vulnerability to backdoor attacks poses critical security risks. Attackers can implant latent triggers that persist through downstream tasks, enabling malicious control ...

An Attack Method for Medical Insurance Claim Fraud Detection Based on Generative Adversarial Network

Insurance fraud detection represents a pivotal advancement in modern insurance service, providing intelligent and digitalized monitoring to enhance management and prevent fraud. It is crucial for ensuring the security and efficiency of insurance systems. Although AI and machine learning algorithm...

SecurityLingua: Efficient Defense of LLM Jailbreak Attacks Via Security-Aware Prompt Compression

Large language models LLMs have achieved widespread adoption across numerous applications. However, many LLMs are vulnerable to malicious attacks even after safety alignment. These attacks typically bypass LLMs' safety guardrails by wrapping the original malicious instructions inside adversarial...

When Forgetting Triggers Backdoors: a Clean Unlearning Attack

Machine unlearning has emerged as a key component in ensuring Right to be Forgotten, enabling the removal of specific data points from trained models. However, even when the unlearning is performed without poisoning the forget-set clean unlearning, it can be exploited for stealthy attacks that...

Doppelgänger Method: Breaking Role Consistency in LLM Agent via Prompt-based Transferable Adversarial Attack

Since the advent of large language models, prompt engineering now enables the rapid, low-effort creation of diverse autonomous agents that are already in widespread use. Yet this convenience raises urgent concerns about the safety, robustness, and behavioral consistency of the underlying prompts,...

From LLMs to MLLMs to Agents: a Survey of Emerging Paradigms in Jailbreak Attacks and Defenses within LLM Ecosystem

Large language models LLMs are rapidly evolving from single-modal systems to multimodal LLMs and intelligent agents, significantly expanding their capabilities while introducing increasingly severe security risks. This paper presents a systematic survey of the growing complexity of jailbreak...

6 Steps to 24/7 In-House SOC Success

Hackers never sleep, so why should enterprise defenses? Threat actors prefer to target businesses during off-hours. That's when they can count on fewer security personnel monitoring systems, delaying response and remediation. When retail giant Marks & Spencer experienced a security event over...

Analyzing PDFs like Binaries: Adversarially Robust PDF Malware Analysis Via Intermediate Representation and Language Model

Malicious PDF files have emerged as a persistent threat and become a popular attack vector in web-based attacks. While machine learning-based PDF malware classifiers have shown promise, these classifiers are often susceptible to adversarial attacks, undermining their reliability. To address this...

Security update for pam

This update for pam fixes the following issues: CVE-2025-6020: pamnamespace: convert functions that may operate on a user-controlled path to operate on file descriptors instead of absolute path. And keep the bind-mount protection from protectmount as a defense in depthmeasure. bsc1244509 Patch...