DCVD: Dual-Channel Cross-Modal Fusion for Joint Vulnerability Detection and Localization

Software vulnerability detection plays a critical role in ensuring system security, where real-world auditing requires not only determining whether a function is vulnerable but also pinpointing the specific lines responsible. However, existing approaches either rely on a single information source...

CVE-2026-37526

AGL app-framework-binder afb-daemon through v19.90.0 allows any local process to execute privileged supervision commands Exit, Do, Sclose, Config, Trace, Debug, Token, slist without authentication via the abstract Unix socket @urn:AGL:afs:supervision:socket. The onsupervisioncall function in...

CVE-2026-37525

AGL app-framework-binder afb-daemon through v19.90.0 contains a privilege escalation vulnerability in the supervision Do command. The onsupervisioncall function in src/afb-supervision.c explicitly nullifies the request credentials by calling afbcontextchangecred&xreq-context, NULL before...

CVE-2026-37526

AGL app-framework-binder afb-daemon through v19.90.0 allows any local process to execute privileged supervision commands Exit, Do, Sclose, Config, Trace, Debug, Token, slist without authentication via the abstract Unix socket @urn:AGL:afs:supervision:socket. The onsupervisioncall function in...

CVE-2026-37525

AGL app-framework-binder afb-daemon through v19.90.0 contains a privilege escalation vulnerability in the supervision Do command. The onsupervisioncall function in src/afb-supervision.c explicitly nullifies the request credentials by calling afbcontextchangecred&xreq-context, NULL before...

CVE-2026-37525

AGL app-framework-binder afb-daemon through v19.90.0 contains a privilege escalation vulnerability in the supervision Do command. The onsupervisioncall function in src/afb-supervision.c explicitly nullifies the request credentials by calling afbcontextchangecred&xreq-;context, NULL before...

PT-2026-36503

Name of the Vulnerable Software and Affected Versions AGL app-framework-binder afb-daemon versions prior to 19.90.1 Description A privilege escalation issue exists in the supervision Do command. The on supervision call function in src/afb-supervision.c nullifies request credentials by calling afb...

EUVD-2026-26681

AGL app-framework-binder afb-daemon through v19.90.0 contains a privilege escalation vulnerability in the supervision Do command. The onsupervisioncall function in src/afb-supervision.c explicitly nullifies the request credentials by calling afbcontextchangecred&xreq-context, NULL before...

CVE-2026-37526

AGL app-framework-binder afb-daemon through v19.90.0 allows any local process to execute privileged supervision commands Exit, Do, Sclose, Config, Trace, Debug, Token, slist without authentication via the abstract Unix socket @urn:AGL:afs:supervision:socket. The onsupervisioncall function in...

CVE-2026-37525

The CVE-2026-37525 entry concerns the AGL app-framework-binder (afb-daemon) up to v19.90.0. The vulnerability resides in the supervision Do command: the on_supervision_call path explicitly_nullifies credentials via afb_context_change_cred(&xreq->context, NULL) before dispatching an attacker-co...

CVE-2026-37525

AGL app-framework-binder afb-daemon through v19.90.0 contains a privilege escalation vulnerability in the supervision Do command. The onsupervisioncall function in src/afb-supervision.c explicitly nullifies the request credentials by calling afbcontextchangecred&xreq-context, NULL before...

SecCodePRM: A Process Reward Model for Code Security

Large Language Models are rapidly becoming core components of modern software development workflows, yet ensuring code security remains challenging. Existing vulnerability detection pipelines either rely on static analyzers or use LLM/GNN-based detectors trained with coarse program-level...

Weak Enforcement and Low Compliance in PCI~DSS: A Comparative Security Study

Although credit and debit card data continue to be a prime target for attackers, organizational adherence to the Payment Card Industry Data Security Standard PCI DSS remains surprisingly low. Despite prior work showing that PCI DSS can reduce card fraud, only 32.4% of organizations were fully...

It’s not personal, it’s just business

Welcome to this week's edition of the Threat Source newsletter. This week, we explore how advances in agentic AI are rapidly transforming the cyber crime business. Agentic AI programming gives AI agents autonomy, allowing them to interact with external systems to collect information, make decisio...

CVE-2025-10696

CVE-2025-10696 affects OpenSupports 4.11.0. An endpoint allows editing the list of 'supervised users' for any account without verifying ownership, enabling a Level 1 staff member to modify the supervision relationship of a target user. This can let the target view tickets belonging to the added s...

HARPT: a Corpus for Analyzing Consumers' Trust and Privacy Concerns in Mobile Health Apps

We present HARPT, a large-scale annotated corpus of mobile health app store reviews aimed at advancing research in user privacy and trust. The dataset comprises over 480,000 user reviews labeled into seven categories that capture critical aspects of trust in applications, trust in providers and...

Shrinking the Generation-Verification Gap with Weak Verifiers

Verifiers can improve language model capabilities by scoring and ranking responses from generated candidates. Currently, high-quality verifiers are either unscalable e.g., humans or limited in utility e.g., tools like Lean. While LM judges and reward models have become broadly useful as...

TED-LaST: Towards Robust Backdoor Defense against Adaptive Attacks

Deep Neural Networks DNNs are vulnerable to backdoor attacks, where attackers implant hidden triggers during training to maliciously control model behavior. Topological Evolution Dynamics TED has recently emerged as a powerful tool for detecting backdoor attacks in DNNs. However, TED can be...

Saffron-1: Towards an Inference Scaling Paradigm for LLM Safety Assurance

Existing safety assurance research has primarily focused on training-phase alignment to instill safe behaviors into LLMs. However, recent studies have exposed these methods' susceptibility to diverse jailbreak attacks. Concurrently, inference scaling has significantly advanced LLM reasoning...

Backdoor Cleaning without External Guidance in MLLM Fine-Tuning

Multimodal Large Language Models MLLMs are increasingly deployed in fine-tuning-as-a-service FTaaS settings, where user-submitted datasets adapt general-purpose models to downstream tasks. This flexibility, however, introduces serious security risks, as malicious fine-tuning can implant backdoors...