CVE-2026-42164

Mahara before 25.04.5 and 26.04.0 is vulnerable in the Text block/section functionality when a call is crafted in a certain way that allows it to recall the backed-up content from another Text section...

CVE-2026-42164

Mahara before 25.04.5 and 26.04.0 is vulnerable in the Text block/section functionality when a call is crafted in a certain way that allows it to recall the backed-up content from another Text section...

CVE-2026-72472 nfs: use nfsi->rwsem to protect traversal of the file lock list

In the Linux kernel, the following vulnerability has been resolved: nfs: use nfsi-rwsem to protect traversal of the file lock list Lingfeng identified a bug and suggested two solutions, but both appear to have issues. Generally, we cannot release flclock while iterating over the file lock list to...

MutMem: Cryptographically Authorized Mutation in Persistent Agent Memory

Persistent agent memory must adapt as later outcomes change earlier evidence, yet mutable retrieval weights create an attribution problem: reviewers must distinguish authorized adaptation from database tampering. We present MutMem, an authorized-mutation protocol in HOM-AIMOS, a persistent...

Cybersecurity Detection Classification with Reasoning-Enabled Language Models

A major issue in Security Operations Centers SOCs is alert fatigue, as the number of detections reported is more than staff can triage in a given day. Prior work prompts or fine-tunes large language models LLMs to emit a triage label directly, but does not train them to reason about whether a...

blockshark

🦈 BlockShark Autonomous exploit-proving engine for smart co...

Evaluating Large Language Models for Symbolic Security Protocol Analysis

Security protocol verification relies on formal tools such as ProVerif and OFMC. This study evaluates whether Large Language Models LLMs can perform comparable analysis. We test GPT and DeepSeek in chat and reasoning modes over three runs on 130 obfuscated AnB/AnBx protocols covering 388 security...

Routing Ceilings Are Domain-Independent: Structural Prior Injection in Code Security Vulnerability Detection

Large language models LLMs exhibit a well-documented gap between latent capability and consistent activation: the router hypothesis posits that models possess the knowledge to solve a task but lack reliable internal routing to activate it. Prior work in formal mathematical reasoning SAIR, C�zares...

PYSEC-2026-2334 aiwaves-cn agents is vulnerable to resource consumption in the recall_relevant_memories_to_working_memory function

A weakness has been identified in aiwaves-cn agents up to e8c4e3c2d19739d3dff59e577d1c97090cc15f59. Affected by this issue is the function recallrelevantmemoriestoworkingmemory of the file core/cat/lookingglass/straycat.py of the component cheshirecatcore. This manipulation causes resource...

aiwaves-cn agents is vulnerable to resource consumption in the recall_relevant_memories_to_working_memory function

A weakness has been identified in aiwaves-cn agents up to e8c4e3c2d19739d3dff59e577d1c97090cc15f59. Affected by this issue is the function recallrelevantmemoriestoworkingmemory of the file core/cat/lookingglass/straycat.py of the component cheshirecatcore. This manipulation causes resource...

PT-2026-59018

A weakness has been identified in aiwaves-cn agents up to e8c4e3c2d19739d3dff59e577d1c97090cc15f59. Affected by this issue is the function recall relevant memories to working memory of the file core/cat/looking glass/stray cat.py of the component cheshire cat core. This manipulation causes resour...

Using LLMs to Adjudicate Static-Analysis Alerts with Error Reduction Techniques

Static analysis is widely used for finding security weaknesses in source code before deployment, but it often produces far more alerts than analysts can review. We study how well large language models LLMs can adjudicate classify as a real bug or a false alarm static-analysis alerts. We use two...

CVE-2026-14630

A vulnerability has been found in ForceInjection AI-fundermentals 2.0/3.0. Affected by this vulnerability is the function getconversationhistory of the file 08agenticsystem/memory/langchain/code/smartcustomerservice.py of the component Memory Recall Handler. The manipulation leads to use of weak...

CVE-2026-14630 ForceInjection AI-fundermentals Memory Recall smart_customer_service.py get_conversation_history weak hash

A vulnerability has been found in ForceInjection AI-fundermentals 2.0/3.0. Affected by this vulnerability is the function getconversationhistory of the file 08agenticsystem/memory/langchain/code/smartcustomerservice.py of the component Memory Recall Handler. The manipulation leads to use of weak...

CVE-2026-14630

ForceInjection AI-fundermentals 2.0/3.0 contains a vulnerability in the Memory Recall Handler: get_conversation_history (08_agentic_system/memory/langchain/code/smart_customer_service.py). The issue involves use of a weak hash, with remote exploitation possible but described as high complexity. E...

CVE-2026-14630 ForceInjection AI-fundermentals Memory Recall smart_customer_service.py get_conversation_history weak hash

A vulnerability has been found in ForceInjection AI-fundermentals 2.0/3.0. Affected by this vulnerability is the function getconversationhistory of the file 08agenticsystem/memory/langchain/code/smartcustomerservice.py of the component Memory Recall Handler. The manipulation leads to use of weak...

CVE-2026-14630: Use of Weak Hash

A vulnerability has been found in ForceInjection AI-fundermentals 2.0/3.0. Affected by this vulnerability is the function getconversationhistory of the file 08agenticsystem/memory/langchain/code/smartcustomerservice.py of the component Memory Recall Handler. The manipulation leads to use of weak...

PT-2026-55707

Name of the Vulnerable Software and Affected Versions ForceInjection AI-fundermentals versions 2.0 through 3.0 Description The Memory Recall Handler component contains an issue within the get conversation history function located in the 08 agentic system/memory/langchain/code/smart customer...

Forensic Trajectory Signatures for Agent Memory Poisoning Detection

We discover a behavioral invariant in LLM agents under persistent memory poisoning: in architectures where routing information is retrieved through observable memory-tool invocations, successful attacks require calling memoryrecallfact before emailsendemail, a transition that non-exfiltrating...

Multi-View Decompilation for LLM-Based Malware Classification

Malware analysts often inspect compiled binaries through decompiled pseudo-C, when source code is unavailable. Recent work suggests that large language models LLMs can assist this process by classifying decompiled code as benign or malicious, but existing pipelines typically rely on a single...