Multiple vulnerabilities in 1millionbot Millie chatbot (CVE-2026-4399)
Published Sources: CVE.org
What is affected, what to do
Prompt injection vulnerability in 1millionbot Millie chatbot that occurs when a user manages to evade chat restrictions using Boolean prompt injection techniques (formulating a question in such a way that, upon receiving an affirmative response ('true'), the model executes the injected instruction), causing it to return prohibited information and information outside its intended context. Successful exploitation of this vulnerability could allow a malicious remote attacker to abuse the service for purposes other than those originally intended, or even execute out-of-context tasks using 1millionbot's resources and/or OpenAI's API key.
Update millie_chatbot to version 3.6.0.
- Affected
- 1millionbot Millie chat
eq 3.6.0..3.6.0
- 1millionbot Millie chat
Not sure whether and how you are affected? Ask a question about this vulnerability
Metrics
8.7
Priority
XIEM Effective CVSS: highest available CVSS rating from NVD and vendor data.
Source: Vendor (CNA), CVSS v4
7.5
CVSS v3
Severity High on the scale from 0 to 10.
Source: CVE.org
0.3 %
EPSS score
Low — model estimates < 1% exploitation likelihood.
Source: FIRST EPSS, percentile 19.1
Show all metrics
- Severity
- High
Priority (0–325)
The priority score is a consolidated metric that condenses several individual signals into a single, action-guiding ranking: technical severity (CVSS), exploitation likelihood (EPSS), known-exploited status (KEV) and the context of the affected asset. The aim is to answer the only truly important question in vulnerability management: what first?
Read in glossary- 62.12 Methodology
Exploit maturity
An exploit is code or a technique that specifically uses a concrete vulnerability to force unintended behaviour — such as executing code or escalating privileges. It is the tool that turns a theoretical flaw into a practical attack.
Read in glossary- no public PoC known
XIEM Effective CVSS
XIEM® is the tiered managed-security operating model from NEOSEC and a registered trademark of NEOSEC GmbH. It extends classic SIEM — the central collection, normalisation and correlation of security-relevant events — with endpoint forensics, network visibility and deception technology, and consolidates them into three building tiers: Sentry, Orchestrate and Command.
Read in glossary- 8.7 Methodology
CVSS v3
CVSS is the globally established, open standard for assessing the technical severity of a vulnerability on a scale from 0 to 10. It describes how easily a flaw can be exploited and what damage it can cause — but not how likely its actual exploitation is. CVSS and the complementary EPSS deliberately answer different questions.
Read in glossary- 7.5
CVSS v4
CVSS is the globally established, open standard for assessing the technical severity of a vulnerability on a scale from 0 to 10. It describes how easily a flaw can be exploited and what damage it can cause — but not how likely its actual exploitation is. CVSS and the complementary EPSS deliberately answer different questions.
Read in glossary- 8.7
EPSS score
The EPSS score is the absolute model output for an individual vulnerability: the estimated probability of real-world exploitation within the next 30 days, expressed as a value between 0 and 1 (i.e. 0 % to 100 %). A score of 0.42 means „the model estimates a 42 % chance of real-world exploitation within 30 days“.
Read in glossary- 0.3 %
- Low — model estimates < 1% exploitation likelihood.
EPSS percentile
The EPSS percentile is the relative position of a vulnerability within all EPSS-scored CVEs, expressed as a value between 0 and 1. A percentile of 0.90 means „this CVE has a higher EPSS score than 90 % of all other scored CVEs“. Unlike the EPSS score, it is not a probability — but a positioning within a ranking.
Read in glossary- 19.1
- Elevated — this CVE ranks above at least 10% of all CVEs scored today.
KEV status
The KEV catalogue is a list maintained by the US authority CISA of vulnerabilities for which active exploitation in the wild has been confirmed. It answers not the question „how severe?“ but „is it already being attacked?“ — thereby sharply prioritising patching.
Read in glossary- —
- Published
- CISA assessment (SSVC)
- Exploitation: none known · automatable · Technical impact: partial
- Source: CISA Vulnrichment, as of 31 March 2026
CWE
CWE is a catalogue of typical weakness types in software and hardware — such as flawed input validation, unsafe memory handling or poor authentication. Where a CVE names a concrete vulnerability in a concrete product, a CWE describes the underlying class of defect.
Read in glossary- CWE-1427
Detection rules
No NEOSEC detection rule is available for this vulnerability yet.
Classification under NIS2 and CRA
Rule-based classification from exploitation status and severity. It does not replace a case-by-case assessment.
NIS2
NIS2 is EU Directive (EU) 2022/2555 to raise the level of cybersecurity across the Union. It substantially broadens obligations compared with the first NIS directive: more sectors, mandatory risk management, staged reporting duties and personal accountability of senior management.
Read in glossary- High technical severity: assess and remediate the vulnerability in vulnerability handling under Art. 21(2)(e) NIS2 and document the decision.
CRA
The CRA is EU Regulation (EU) 2024/2847 setting horizontal cybersecurity requirements for „products with digital elements“ — from industrial controllers and software to connected consumer devices. For the first time manufacturers must ensure security across the entire product lifecycle, handle vulnerabilities and provide security updates.
Read in glossary- From 11.12.2027, Annex I Part II CRA requires manufacturers of affected products with digital elements to handle vulnerabilities without delay and provide security updates.
ISO/IEC 27001
ISO/IEC 27001 is the internationally leading standard for an information security management system (ISMS). It describes a risk-based, process-oriented framework to systematically plan, implement, review and improve information security.
Read in glossary- Control A.8.8, management of technical vulnerabilities: assess relevance to your systems, plan remediation and keep evidence.
Description
Prompt injection vulnerability in 1millionbot Millie chatbot that occurs when a user manages to evade chat restrictions using Boolean prompt injection techniques (formulating a question in such a way that, upon receiving an affirmative response ('true'), the model executes the injected instruction), causing it to return prohibited information and information outside its intended context. Successful exploitation of this vulnerability could allow a malicious remote attacker to abuse the service for purposes other than those originally intended, or even execute out-of-context tasks using 1millionbot's resources and/or OpenAI's API key. This allows the attacker to evade the containment mechanisms implemented during LLM model training and obtain responses or chat behaviors that were originally restricted.
Source: NVD (NIST), cvelistv5
Affected products
The following versions are affected. Older releases of the same product line are also vulnerable unless stated otherwise.
| Affected versions | Fixed in | ||
|---|---|---|---|
| 1millionbot | Millie chat |
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| 1millionbot | millie_chatbot |
|
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Weakness classes (CWE)
CWE-1427Improper Neutralization of Input Used for LLM Prompting
Base
The product uses externally-provided data to build prompts provided to large language models (LLMs), but the way these prompts are constructed causes the LLM to fail to distinguish between user-supplied inputs and developer provided system directives.
Entry at MITRE CWE-1427
References & sources
- incibe.esen/incibe-cert/notices/aviso/multiple-vulnerabilities-1millionb…Third-party advisory
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<a href="https://intel.neosec.eu/en/cve/CVE-2026-4399"><img src="https://intel.neosec.eu/badge/cve/CVE-2026-4399.svg?lang=en" alt="CVE-2026-4399 – NEOSEC Intel" height="20"></a>