CVE-2024-5206VulnerabilityPublished 6 Jun 2024Updated 9 Nov 2026

A sensitive data leakage vulnerability was identified in scikit-learn's TfidfVectorizer, specifically in versions up

Affects scikit-learnSource GCVE Database

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Not known to be exploited · CVSS 4.7 Medium · fixed in 1.5.0 : update scikit-learn when convenient.

Data as of 9 Nov 2026, 14:36 UTC

CVSS 3.0 base score

4.7Medium

How severe the flaw is on the 0–10 CVSS scale.

Patch: Available – fixed in 1.5.0

CVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:N/A:N

Attack Vector: Local
Attack Complexity: High
Privileges Required: Low
User Interaction: None
Scope: Unchanged
Confidentiality: High
Integrity: None
Availability: None

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Local: The vulnerable component is not bound to the network stack and the attacker’s path is via read/write/execute capabilities. Either: the attacker exploits the vulnerability by accessing the target system locally (e.g., keyboard, console), or remotely (e.g., SSH); or the attacker relies on User Interaction by another person to perform actions required to exploit the vulnerability (e.g., tricking a legitimate user into opening a malicious document).
Attack Complexity: High: A successful attack depends on conditions beyond the attacker's control. That is, a successful attack cannot be accomplished at will, but requires the attacker to invest in some measurable amount of effort in preparation or execution against the vulnerable component before a successful attack can be expected. For example, a successful attack may require an attacker to: gather knowledge about the environment in which the vulnerable target/component exists; prepare the target environment to improve exploit reliability; or inject themselves into the logical network path between the target and the resource requested by the victim in order to read and/or modify network communications (e.g., a man in the middle attack).
Privileges Required: Low: The attacker is authorized with (i.e., requires) privileges that provide basic user capabilities that could normally affect only settings and files owned by a user. Alternatively, an attacker with Low privileges may have the ability to cause an impact only to non-sensitive resources.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: High: There is total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact.
Integrity: None: There is no loss of integrity within the impacted component.
Availability: None: There is no impact to availability within the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 6 Jun 2024
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 9 Nov 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponized: A Metasploit exploit module or Exploit-DB entry exists (Metasploit scanner modules do not count), or CISA SSVC or the CVSS exploit maturity reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Affected software

Product	Affected	Fixed in
Ubuntu 26.10scikit-learn`pkg:deb/ubuntu/scikit-learn?arch=source&distro=stonking`Other threats	Affected =1.7.2+dfsg-4build1 =1.9.0+dfsg-1	Fixed in–
Ubuntu 25.10scikit-learn`pkg:deb/ubuntu/scikit-learn?arch=source&distro=questing`Other threats	Affected =1.4.2+dfsg-8	Fixed in–
Ubuntu 24.04 LTSscikit-learn`pkg:deb/ubuntu/scikit-learn?arch=source&distro=noble`Other threats	Affected 1.2.1+dfsg-1build1 – 1.4.1.post1+dfsg-1build1 4 affected builds	Fixed in–
Ubuntu 22.04 LTSscikit-learn`pkg:deb/ubuntu/scikit-learn?arch=source&distro=jammy`Other threats	Affected =0.23.2-5ubuntu2 =0.23.2-5ubuntu4 =0.23.2-5ubuntu6	Fixed in–
Ubuntu 20.04 LTSscikit-learn`pkg:deb/ubuntu/scikit-learn?arch=source&distro=focal`Other threats	Affected =0.20.3+dfsg-0ubuntu2 =0.20.3+dfsg-0ubuntu3 =0.22.2.post1+dfsg-5	Fixed in–
Ubuntu 18.04 LTSscikit-learn`pkg:deb/ubuntu/scikit-learn?arch=source&distro=bionic`Other threats	Affected 0.19.0-1build1 – 0.19.1-3 4 affected builds	Fixed in–

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

Upgrade scikit-learn to version 1.5.0 or later, where this vulnerability has been fixed. No other mitigation actions are indicated.

Description

A sensitive data leakage vulnerability exists in scikit-learn's TfidfVectorizer up to and including version 1.4.1.post1. The issue is due to the `stop_words_` attribute storing all tokens from the training data rather than only the necessary subset, potentially exposing sensitive tokens such as passwords or keys. This vulnerability was fixed in version 1.5.0. The impact depends on the nature of the data processed by the vectorizer.

Impact

Sensitive data present in the training dataset may be exposed through the `stop_words_` attribute of the TfidfVectorizer object. The severity of the impact depends on whether sensitive tokens were included in the training data. There is no indication of integrity or availability impact. The CVSS score is 4.7 (medium severity), reflecting local attack vector, high complexity, low privileges required, no user interaction, and high confidentiality impact.

Summary

The vulnerability in scikit-learn's TfidfVectorizer affects versions up to and including 1.4.1.post1. The `stop_words_` attribute unexpectedly retains all tokens from the training data instead of only those required for TF-IDF computation. This behavior can lead to leakage of sensitive information if the training data contains confidential tokens like passwords or keys. The issue was addressed and fixed in version 1.5.0.

References

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