Exploitation observed; activity peaked at 28 mentions and remains active
Immediate actions
Patch ollama ollama systems immediately
Assume compromise if assets are exposed
Hunt for exploitation attempts and persistence artifacts
Increase monitoring for publicly documented tradecraft
Recommended action window: Immediate (within 24h)
NVD description
Ollama before 0.17.1 contains a heap out-of-bounds read vulnerability in the GGUF model loader. The /api/create endpoint accepts an attacker-supplied GGUF file in which the declared tensor offset and size exceed the file's actual length; during quantization in fs/ggml/gguf.go and server/quantization.go (WriteTo()), the server reads past the allocated heap buffer. The leaked memory contents may include environment variables, API keys, system prompts, and concurrent users' conversation data, and can be exfiltrated by uploading the resulting model artifact through the /api/push endpoint to an attacker-controlled registry. The /api/create and /api/push endpoints have no authentication in the upstream distribution. Default deployments bind to 127.0.0.1, but the documented OLLAMA_HOST=0.0.0.0 configuration is widely used in practice (large public-internet exposure observed).
Active Exploitation6Disclosure11Exploit1General2Patch8
2026-05-11
24
Active Exploitation1Disclosure8Exploit1General4Patch10
2026-05-12
10
Active Exploitation1Disclosure2General2Patch5
2026-05-14
2
Disclosure1General1
2026-05-15
7
Disclosure3General4
2026-05-16
1
Patch1
2026-05-17
2
Disclosure1Patch1
2026-05-18
2
Active Exploitation1Patch1
2026-05-24
3
Disclosure1General2
2026-05-26
1
Patch1
2026-05-27
2
General1Patch1
2026-06-02
1
Patch1
2026-06-04
3
Active Exploitation1Disclosure1Patch1
2026-06-08
5
Disclosure4General1
2026-06-13
3
Disclosure1General1Patch1
2026-06-19
4
Disclosure4
2026-06-22
1
Disclosure1
2026-06-26
1
Disclosure1
2026-07-02
1
Active Exploitation1
2026-07-05
1
PoC1
2026-07-16
1
Patch1
2026-07-21
1
Patch1
2026-07-24
1
General1
2026-08-02
1
Active Exploitation1
2026-08-05
1
Patch1
2026-08-06
1
Disclosure1
2026-08-13
1
Active Exploitation1
2026-08-26
1
Disclosure1
2026-09-20
1
Patch1
>Full discourse20 posts
The Hacker News@TheHackersNews·
Disclosure
🚨 CVE-2026-7482 in Ollama could let remote attackers leak process memory from more than 300,000 exposed servers using crafted GGUF files.
Separate unpatched Windows flaws enable persistent code execution through Ollama’s update mechanism.
Full details and mitigations: https://thehackernews.com/2026/05/ollama-out-of-bounds-read-vulnerability.html
Post summary
CVE-2026-7482 in Ollama is an out-of-bounds read that could allow remote attackers to leak process memory from over 300,000 exposed servers; mitigations are available via the linked article.
local AI katanya lebih aman
karena datanya ga kemana-mana
tinggal di laptop sendiri
ternyata tidak selalu 👀
"Bleeding Llama" — CVE-2026-7482, CVSS 9.1
celah kritis di Ollama yang bisa bocorkan semua yang lo pikir aman
thread buat yang pake Ollama, Claude Code, atau coding agent 👇
Post summary
The post announces a newly disclosed critical vulnerability (CVE-2026-7482) in Ollama with a high CVSS score, warning that it could leak sensitive data but provides no exploit details or patch information.
> run Claude Code root-level on your computer
> paste in the following prompt:
Audit my MacBook for exposure to the Ollama vulnerabilities disclosed on May 10, 2026 (CVE-2026-7482 "Bleeding Llama" — heap out-of-bounds read in GGUF loader on `/api/create`, fixed in 0.17.1; and CVE-2026-42248 / CVE-2026-42249 — Windows-only updater flaws affecting 0.12.10–0.22.0, can be skipped since this is macOS but confirm no Windows VM/Parallels instance is running Ollama) and produce a single concise final report — do not fix anything, only diagnose. Specifically: (1) check if Ollama is installed and get its version with `ollama --version` and `which ollama`, then compare against 0.17.1 to determine if the GGUF flaw applies; (2) determine whether the Ollama server is currently running and on what interface — run `lsof -nP -iTCP:11434 -sTCP:LISTEN` and `ps aux | grep -i ollama` to see if it's bound to `127.0.0.1` (safe, loopback only) or `0.0.0.0`/`*` (listening on all interfaces, network-reachable); (3) check the launch environment for `OLLAMA_HOST` — inspect `launchctl getenv OLLAMA_HOST`, `~/.zshrc`, `~/.zprofile`, `~/.bash_profile`, `~/.bashrc`, and any LaunchAgents/LaunchDaemons under `~/Library/LaunchAgents` and `/Library/LaunchAgents` for persistent `OLLAMA_HOST=0.0.0.0` settings; (4) determine the local network exposure layer — get the LAN IP with `ifconfig | grep "inet "`, check the macOS application firewall state with `/usr/libexec/ApplicationFirewall/socketfilterfw --getglobalstate` and whether Ollama is allowed/blocked, and note that even if bound to `0.0.0.0` the box is only LAN-reachable unless the upstream router forwards port 11434 (which the agent cannot verify from inside the host — flag this as a manual check); (5) check for any reverse proxy, Tailscale, ngrok, Cloudflare Tunnel, or similar tunneling tool that could expose 11434 publicly — run `ps aux | grep -E "ngrok|cloudflared|tailscaled|frp"` and `ls ~/Library/LaunchAgents`; (6) confirm no Windows Ollama instance is running in a Parallels/VMware/UTM VM by listing running VMs if any virtualization software is installed. Then output one short final report with: Ollama version + vulnerable yes/no, listening interface (loopback vs all), `OLLAMA_HOST` env state, LAN IP, tunneling tools detected, and a one-line verdict — "likely affected", "only-if-router-forwards-11434", or "not affected" — plus the single most important action to take. Do not modify any files, do not stop or start Ollama, do not change firewall rules.
Post summary
The post provides a step‑by‑step guide to audit a MacBook’s Ollama installation for exposure to known CVEs, checks version, server binding, environment variables, network exposure, and tunneling tools, culminating in a concise verdict and recommended action.
300,000 exposed Ollama servers run unauthenticated, no login needed. Bleeding Llama (CVE-2026-7482) dumps full memory, including AWS keys, in three API calls.
https://www.cybersecurityintelligence.com/blog/the-unmanaged-ai-edge-9504.html
Post summary
The post highlights a discovered CVE that exposes unprotected Ollama servers, demonstrating a memory‑dump PoC that retrieves AWS keys, but no active exploitation or patch info is given.
🚨Alert🚨 CVE-2026-7482 : Ollama Out-of-Bounds Read Vulnerability Allows Remote Process Memory Leak.
🧐Deep Dive
:https://www.cyera.com/research/bleeding-llama-critical-unauthenticated-memory-leak-in-ollama
📊 1.1M+ Services are found on the http://hunter.how yearly.
🔗Hunter
Link:https://hunter.how/list?searchValue=product.name%3D%22Ollama%20Server%22
👇Query
HUNTER : http://product.name="Ollama Server"
📰Refer:https://thehackernews.com/2026/05/ollama-out-of-bounds-read-vulnerability.html
#hunterhow#infosec#infosecurity#OSINT#Vulnerability
Post summary
An alert announcing CVE‑2026‑7482, describing it as an out‑of‑bounds read that leaks remote process memory, with links to research and a news article but no PoC, exploit code, active exploitation, or patch details.
CVE‑2026‑7482, a severe unauthenticated memory‑read flaw in Ollama, has been disclosed; users are urged to update to the latest version and tighten external access to mitigate the risk.
Local AI is only private if the API stays private.
The recent Ollama vulnerability is a good reminder.
CVE-2026-7482, patched in Ollama 0.17.1, was a heap out-of-bounds read in the GGUF model loader. The exploit path matters:
A crafted model hits `/api/create`, memory gets read past the buffer, sensitive process data can land inside the model artifact, and `/api/push` can send it out.
Cyera said the leaked data could include prompts, system prompts, environment variables, API keys, and conversation data.
That changes how you should think about "local" AI.
If Ollama is bound to localhost, you have a local model server.
If port `11434` is exposed to the internet without auth, you have an unauthenticated inference API with secrets in memory.
My default checklist:
- update Ollama to 0.17.1+
- keep it on localhost by default
- don't expose raw `11434`
- use Tailscale, WireGuard, firewall allowlists, or an auth proxy for remote access
- rotate secrets if the instance was exposed before patching
Local models are still a great way to control data.
But treat the model server like infrastructure, not a toy dev server.
Post summary
The post highlights CVE‑2026‑7482 as a heap out‑of‑bounds read in Ollama, details the exploit path, and stresses the importance of patching to 0.17.1 along with practical mitigations.
🚨 Acaba de confirmarse: una vulnerabilidad crítica en Ollama permite a un atacante remoto y no autenticado filtrar la memoria completa del proceso, afectando potencialmente a más de 300,000 servidores en todo el mundo.
La vulnerabilidad, identificada como CVE-2026-7482, es un out-of-bounds read en el parser de archivos GGUF de Ollama, que podría permitir a un atacante leer arbitrariamente la memoria del proceso, incluyendo claves API, rutas y secretos.
El ataque puede ser desencadenado mediante una solicitud POST a `/api/generate` o `/api/copy` con un payload GGUF manipulado, lo que permite al atacante leer ~4KB de memoria heap por solicitud.
El equipo de Ollama ha parcheado la vulnerabilidad en la versión 0.3.13, por lo que es importante que los usuarios actualicen su software lo antes posible. ¿Estás en riesgo? Revisa esto: actualiza Ollama a la versión 0.3.13 o posterior para evitar la explotación de esta vulnerabilidad.
https://thehackernews.com/2026/05/ollama-out-of-bounds-read-vulnerability.html
Post summary
The post alerts about CVE‑2026‑7482, an out‑of‑bounds read in Ollama’s GGUF parser, warns the potential for memory leakage via POST requests, and urges users to install the 0.3.13 patch to mitigate the risk.
로컬에서 돌린다고 안심하던 Ollama 서버 30만 대가 GGUF 파일 하나로 메모리 다 털리게 생겼음. CVE-2026-7482 취약점 터진 건데, 윈도우 사용자들은 업데이트 메커니즘 통해서 아예 코드 실행 권한까지 넘겨줄 판임. 빨리 지우던지 업데이트 하던지 하세요.
Post summary
CVE-2026-7482 triggers a memory‑exhaustion attack on Ollama servers via a single GGUF file, potentially leading to code execution through the Windows update process; users are urged to delete or update to mitigate the vulnerability.
A critical Ollama vulnerability just made every exposed self-hosted LLM deployment a live exfiltration risk.
Bleeding Llama. CVE-2026-7482. CVSS 9.1.
No authentication required. An attacker sends a crafted GGUF model file and starts pulling sensitive process memory off your server. API keys, environment variables, conversation data, prompts. Whatever is in memory at the time.
The attack surface is enormous. Reports suggest potentially hundreds of thousands of Ollama instances are directly reachable from the internet right now.
Here is the part that should concern backend engineers specifically.
Teams spin up local LLMs, assume the inference layer is internal, and move on. No reverse proxy. No auth. No monitoring. Just raw Ollama sitting on a port, doing its job, until it is doing someone else’s job too.
In 2026, exposed AI inference infrastructure is part of your attack surface whether you treat it that way or not.
The fix is not complicated but it requires you to actually do it.
Upgrade to Ollama v0.17.1 or later. Never expose Ollama directly to the public internet. Put authentication and a reverse proxy in front of every inference service.
Restrict GGUF uploads to trusted sources only. Disable public model creation endpoints. Run inference in isolated containers. Monitor your /api/create and /api/push activity for anything unusual. Rotate your secrets if you have ever run a vulnerable exposed instance.
If you are not sure whether your deployment is exposed, assume it is and check.
My name is Azubuike Ibe and I write about the security gaps that open up when teams move fast with AI infrastructure and assume someone else already handled the hardening.
Comment “BLEEDINGLLAMA” and I will send you my Ollama and self-hosted LLM hardening playbook with secure deployment patterns for backend services. Follow me first so the DM reaches you.
Are you still running Ollama or similar tooling exposed to the internet?
#Cybersecurity#AISecurity#LLMSecurity#Ollama#DevSecOps
Post summary
The post highlights a high‑severity vulnerability in Ollama (CVE‑2026‑7482) and focuses on actionable mitigation steps, such as upgrading to v0.17.1, adding authentication and reverse proxies, and disabling public endpoints.
The provided text only names CVE‑2026‑7482 (“Bleeding Llama”) and includes a short tweet link, offering no additional details on exploitation, patches, or vulnerability specifics.
CVE-2026-7482
⚠️ Ollama – Remote Process Memory Leak via GGUF Parsing (CVSS 9.1)
A critical heap out-of-bounds read vulnerability in Ollama's GGUF loader (versions prior to 0.17.1) allows unauthenticated attackers to remotely leak process memory by uploading a crafted GGUF file to the /api/create endpoint. The flaw exists in the GGUF model loader, where attacker-controlled tensor offset and size can trigger reads past allocated heap buffers during quantisation. Exposed memory may include API keys, prompts, credentials, model data, and active user conversations.
Mitigation: Update to Ollama 0.17.1 immediately.
Modat Magnify Query:
product="Ollama"
The platform:
https://magnify.modat.io/
#threatintel#vulnerability#CVE20267482#Ollama#LLM#AIsecurity#infosec#Critical#ModatMagnify
Post summary
A new critical heap OOB read vulnerability (CVE‑2026‑7482) in Ollama’s GGUF loader allows attackers to leak process memory via a crafted file. The vendor recommends updating to version 0.17.1 to mitigate the risk.
A critical vulnerability in Ollama (CVE-2026-7482) is putting local LLM deployments at risk of remote memory leaks. With a CVSS score of 9.9, unauthenticated attackers can exploit the GGUF loader to exfiltrate sensitive data like API keys and system prompts. Upgrade to version 0.17.1 immediately and use Qualys to detect vulnerable assets in your environment.
Read the full threat analysis: https://bit.ly/48TOpfi
#Ollama#CyberSecurity#LLM#Qualys
Post summary
The post highlights a critical memory‑leak vulnerability in Ollama that allows unauthenticated attackers to exfiltrate sensitive information, and it urges users to upgrade to version 0.17.1 and employ Qualys for detection.
CVE-2026-7482, "Bleeding Llama"
severity score: 9.1 dari 10
cara kerjanya simpel dan mengerikan:
attacker kirim file model GGUF palsu
lewat endpoint /api/create
yang ga dilindungi auth apapun
Ollama baca file itu
terjadi out-of-bounds read
memori proses Ollama bocor ke attacker
selesai
tanpa password
tanpa exploit rumit
cukup kirim file palsu
Post summary
The post describes a high‑severity out‑of‑bounds read in Ollama’s unprotected /api/create endpoint that can leak memory, but it does not provide a PoC, exploit code, or evidence of active attacks.
Una vulnerabilitat al GGUF, el format obert que empaqueta models d'IA en un sol fitxer i que Ollama utilitza, exposa prompts, missatges i variables d'entorn d'unes 300.000 instàncies exposades a internet. Puntuació 9.3/10 (CVE-2026-7482).
https://www.securityweek.com/critical-bug-could-expose-300000-ollama-deployments-to-information-theft/
Post summary
A newly disclosed CVE-2026-7482 reveals a high‑severity vulnerability in the GGUF format used by Ollama, potentially exposing prompts, messages, and environment variables from up to 300,000 internet‑exposed instances.
A critical vulnerability in Ollama (CVE-2026-7482) is putting local LLM deployments at risk of remote memory leaks. With a CVSS score of 9.9, unauthenticated attackers can exploit the GGUF loader to exfiltrate sensitive data like API keys and system prompts. Upgrade to version 0.17.1 immediately and use Qualys to detect vulnerable assets in your environment.
Read the full threat analysis: https://bit.ly/48TOpfi
#Ollama#CyberSecurity#LLM#Qualys
Post summary
The post warns about a critical CVE-2026-7482 affecting Ollama, highlighting remote memory leaks and urging users to upgrade to version 0.17.1 and use Qualys for detection.
The tweet alerts that CVE‑2026‑7482 affects Ollama’s Bleeding Llama, noting that roughly 300,000 instances were exposed publicly, but offers no proof‑of‑concept, exploit, patch, or detailed technical info.
300K+ Ollama servers leaking process memory and nobody noticed until now. CVE-2026-7482 is a heap out-of-bounds read in the GGUF model loader.
You feed it a crafted model file, it reads past the buffer, and out comes API keys, environment variables, other users' conversations.
The /api/create and /api/push endpoints have zero auth by default. And how many setups bind to 0.0.0.0 because the docs say to? Too many. Update to 0.17.1 or check your OLLAMA_HOST binding. Now.
https://thehackernews.com/2026/05/ollama-out-of-bounds-read-vulnerability.html
Post summary
CVE‑2026‑7482 causes a heap out‑of‑bounds read in Ollama’s GGUF loader, allowing attackers to read sensitive data from around 300,000 unsecured servers, which has been actively exploited; applying the 0.17.1 update or securing the bind address mitigates the vulnerability.
