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VU#951662: MuPDF by Artifex contains integer overflow vulnerability.
Artifex's MuPDF contains an integer overflow vulnerability, CVE-2026-3308, in versions up to and including 1.27.0. Using a specially crafted PDF, an attacker can trigger an integer overflow resulting in out-of-bounds heap writes. This heap corruption typically causes the application to crash, but in some cases could be exploited to enable arbitrary code execution.
DescriptionArtifex MuPDF is a lightweight framework for viewing and converting PDF, XPS, and e-book files. A vulnerability exists in pdf_load_image_imp, which is responsible for preparing image data for decoding.
The function processes image parameters including w (width), h (height), and bpc (bits per component), which are used to determine the amount of memory allocated during image decoding. The current implementation validates these parameters against SIZE_MAX rather than INT_MAX, but because stride calculations use integer-sized values, this check does not sufficiently protect against integer overflow when exceedingly large values are supplied.
When the overflow occurs, the resulting corrupted values are passed into the fz_unpack_stream function, which expands packed image samples into a destination buffer during image decoding. Because this too-small overflow value is used to calculate the size of the destination buffer, not enough memory is allocated for the actual size of the image. This causes fz_unpack_stream to write beyond the bounds of the allocated heap buffer, resulting in a heap out-of-bounds write.
ImpactSuccessful exploitation results in a heap out-of-bounds write during PDF image decoding. This condition may cause application crashes and memory corruption, or could potentially allow arbitrary code execution within the context of the application rendering the PDF. Since this vulnerability is triggered during standard PDF parsing operations, any system that automatically processes or renders untrusted PDF files using MuPDF may be affected.
SolutionUnfortunately, the vendor was unreachable to coordinate this vulnerability. Until a complete fix is available, users should avoid processing untrusted PDF files with affected MuPDF-based applications where possible. Applications that rely on MuPDF should isolate document rendering in a sandboxed or low-privilege process and disable automatic rendering or conversion of untrusted files if feasible. A Pull Request (PR) was with the fix is available at: https://github.com/ArtifexSoftware/mupdf/pull/87
AcknowledgementsThanks toYarden Porat from Cyata for reporting this vulnerability. This document was written by Michael Bragg.
CVE-2026-3308 An integer overflow vulnerability in 'pdf-image.c' in Artifex's MuPDF version 1.27.0 allows an attacker to maliciously craft a PDF that can trigger an integer overflow within the 'pdf_load_image_imp' function. This allows a heap out-of-bounds write that could be exploited for arbitrary code execution.
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VU#655822: Kyverno is vulnerable to server-side request forgery (SSRF)
Kyverno, versions 1.16.0 to present, contains an SSRF vulnerability in its CEL-based HTTP functions, which lack URL validation or namespace scoping and allow namespaced policies to trigger arbitrary internal HTTP requests. An attacker with only namespace-level permissions can exploit this to access sensitive internal services via the highly privileged Kyverno admission controller.
DescriptionKyverno is an open-source, Kubernetes-native policy engine that functions as a dynamic admission controller for the Kubernetes API. It is designed to manage the lifecycle of cluster resources by validating, mutating, and generating configurations based on YAML-defined policies. Within a security context, the engine is frequently utilized to enforce Pod Security Standards, verify image signatures via Cosign, and audit resource configurations for compliance. Because Kyverno operates with high-level permissions to intercept and modify API requests, it represents a critical component of the cluster's security posture and trust boundary.
A server-side request forgery vulnerability exists in Kyverno’s CEL-based HTTP functions (Get and Post) used by namespaced policy types in the policies.kyverno.io API group. Unlike Kyverno’s resource library, which enforces namespace boundaries, the HTTP library at pkg/cel/libs/http/http.go performs no URL validation or scoping; i.e., there are no blocklists, namespace restrictions, or destination checks. As a result, these policies can issue arbitrary HTTP requests from the Kyverno admission controller pod.
ImpactAn authenticated attacker with only namespace-scoped permissions can create a malicious namespaced policy that sends an internal http.Get() request, captures the response in a CEL variable, and exfiltrates it via the policy’s messageExpression field returned in the admission denial. Because requests originate from the Kyverno admission controller, which often has privileged network reachability across internal cluster services and cloud metadata APIs, this enables cross-namespace data access and potential exposure of sensitive metadata or service responses, effectively breaking Kyverno’s intended security boundaries through SSRF.
SolutionUnfortunately, we were unable to reach the vendor to coordinate this vulnerability. Since a patch is unavailable, we can only offer mitigation strategies.
Mitigation should include implementing strict URL validation and destination controls within Kyverno’s CEL HTTP library to ensure parity with the namespace-scoped restrictions enforced by the resource library. Recommended safeguards include blocking access to link-local and cloud metadata address ranges, limiting outbound requests to approved in-cluster services, and providing administrators with configurable allowlists. Additionally, applying default deny network policies to the Kyverno admission controller pod can reduce residual risk by preventing unauthorized egress in the event of future validation gaps.
AcknowledgementsThanks to Igor Stepansky from Orca Security Research Pod for responsibly disclosing this vulnerability. This document was written by Dr. Elke Drennan, CISSP.
