CVE-2024-9774VulnerabilityPublished 27 Dec 2024Updated 30 Aug 2025

CVE-2024-9774: python-sql · Improper Neutralization of Escape, Meta, or Control Sequences

Affects python-sqlSource CVE Database V5

Not known to be exploited · CVSS 6.5 Medium.

Data as of 26 Oct 2026, 08:30 UTC

CVSS 3.0 base score

6.5Medium

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

EPSS: 0.6% chance of exploitation in 30 days – higher than 52% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

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

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

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

Attack Vector: Network: The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed, up to and including the entire Internet. Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: High: The attacker is authorized with (i.e., requires) privileges that provide significant (e.g., administrative) control over the vulnerable component that could affect component-wide settings and files.
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: High: There is a total loss of integrity, or a complete loss of protection. For example, the attacker is able to modify any/all files protected by the impacted component. Alternatively, only some files can be modified, but malicious modification would present a direct, serious consequence to 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 27 Dec 2024
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: 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 26 Oct 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.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC 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
PyPIpython-sql`pkg:pypi/python-sql`Other threats	Affected =0	Fixed in–

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

AI-suggested

To mitigate CVE-2024-9774, organizations should first monitor for updates or patches from the python-sql maintainers and apply them promptly once available. Until patches are released, developers should avoid passing non-Expression inputs to unary operators or implement strict input validation and sanitization to ensure all inputs are properly escaped. Code audits focusing on the use of python-sql unary operators can identify risky usage patterns. Limiting the privileges of accounts and services that interact with the database reduces the potential impact of exploitation. Employing database-level access controls and query parameterization can further mitigate risks. Additionally, monitoring database logs for unusual query patterns or anomalies may help detect exploitation attempts. Organizations should also consider isolating critical database systems and enforcing network segmentation to limit exposure. Finally, educating developers about secure usage of SQL construction libraries and the risks of improper input handling is essential for long-term risk reduction.

Description

A vulnerability was found in python-sql where unary operators do not escape non-Expression.

Impact

The primary impact of CVE-2024-9774 is on the confidentiality and integrity of data managed by applications using the python-sql library. Exploitation could allow attackers with high privileges to inject malicious SQL sequences or manipulate queries, leading to unauthorized data disclosure or alteration. Although availability is not affected, the breach of confidentiality and integrity can have serious consequences, including data leaks, corruption, or unauthorized transactions. Organizations that rely on python-sql for database interactions, especially in sensitive environments such as finance, healthcare, or government, face elevated risks. The requirement for high privileges limits the attack surface but also indicates that compromised or insider accounts could leverage this vulnerability to escalate damage. The absence of known exploits reduces immediate risk but does not eliminate the threat, especially as attackers may develop exploits once the vulnerability becomes widely known. The lack of patches at disclosure time necessitates proactive mitigation to prevent potential exploitation.

References

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