VulnerabilityPublished 17 Jun 2025

CVE-2025-49149: langgenius dify · Cross-site Scripting

Affects langgenius difySource CVE Database V5

Not known to be exploited · CVSS 5.3 Medium.

Data as of 26 Oct 2026, 14:05 UTC

CVSS 4.0 base score

5.3Medium

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

EPSS: 0.2% chance of exploitation in 30 days – higher than 20% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.

CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:N/VI:N/VA:N/SC:N/SI:L/SA:N

Attack Vector: Network
Attack Complexity: Low
Attack Requirements: None
Privileges Required: None
User Interaction: Passive
Vulnerable system confidentiality: None
Vulnerable system integrity: None
Vulnerable system availability: None
Subsequent system confidentiality: None
Subsequent system integrity: Low
Subsequent system availability: None

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

Attack Vector: Network: The vulnerable system is bound to the network stack and the set of possible attackers extends beyond the other options listed below, 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: The attacker must take no measurable action to exploit the vulnerability. The attack requires no target-specific circumvention to exploit the vulnerability. An attacker can expect repeatable success against the vulnerable system.
Attack Requirements: None: The successful attack does not depend on the deployment and execution conditions of the vulnerable system. The attacker can expect to be able to reach the vulnerability and execute the exploit under all or most instances of the vulnerability.
Privileges Required: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files of the vulnerable system to carry out an attack.
User Interaction: Passive: Successful exploitation of this vulnerability requires limited interaction by the targeted user with the vulnerable system and the attacker’s payload. These interactions would be considered involuntary and do not require that the user actively subvert protections built into the vulnerable system.
Vulnerable system confidentiality: None: There is no loss of confidentiality within the Vulnerable System.
Vulnerable system integrity: None: There is no loss of integrity within the Vulnerable System.
Vulnerable system availability: None: There is no impact to availability within the Vulnerable System.
Subsequent system confidentiality: None: There is no loss of confidentiality within the Subsequent System or all confidentiality impact is constrained to the Vulnerable System.
Subsequent system integrity: Low: Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact to the Subsequent System.
Subsequent system availability: None: There is no impact to availability within the Subsequent System or all availability impact is constrained to the Vulnerable System.

Definitions: FIRST CVSS v4.0 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 17 Jun 2025
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 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
GitHublanggenius/dify`pkg:github/langgenius/dify`Other threats	Affected =1.2.0	Fixed in–

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

AI-suggested

Immediate mitigation should focus on input validation and output encoding: Implement strict server-side input sanitization to neutralize potentially malicious characters or scripts before rendering user input in web pages.
Employ Content Security Policy (CSP) headers to restrict the execution of unauthorized scripts and reduce the impact of injected code.
Use web application firewalls (WAFs) configured with rules to detect and block common XSS attack patterns targeting Dify endpoints.
Restrict user privileges and session lifetimes to limit the window of opportunity for attackers leveraging stolen credentials.
Monitor web application logs for unusual input patterns or repeated injection attempts to identify potential exploitation attempts early.
Engage with the langgenius community or maintainers to track patch releases and apply updates promptly once available.
For organizations with development capabilities, consider contributing or implementing temporary patches or filters to sanitize inputs in the affected version.
Educate users about the risks of clicking on suspicious links or interacting with untrusted content within applications built on Dify.
Isolate Dify deployments in segmented network zones to limit lateral movement if exploitation occurs. These measures go beyond generic advice by focusing on immediate protective controls tailored to the nature of the vulnerability and the platform’s usage context.

Description

Dify is an open-source LLM app development platform. In version 1.2.0, there is insufficient filtering of user input by web applications. Attackers can use website vulnerabilities to inject malicious script code into web pages. This may result in a cross-site scripting (XSS) attack when a user browses these web pages. At time of posting, there is no known patched version.

Impact

For European organizations using Dify 1.2.0, this vulnerability poses a risk primarily to the confidentiality and integrity of user sessions and data accessed through affected web applications. Attackers could exploit the XSS flaw to steal session cookies, impersonate users, or perform unauthorized actions within the context of the vulnerable application. This can lead to data leakage, unauthorized access to sensitive information, or manipulation of application behavior. Organizations deploying Dify in customer-facing or internal portals may face reputational damage, regulatory scrutiny under GDPR if personal data is compromised, and operational disruption if trust in the platform is undermined. The impact is heightened for sectors with high reliance on web-based AI tools, such as financial services, healthcare, and public administration, where sensitive data and compliance requirements are stringent. However, since exploitation requires user interaction and no privilege escalation is involved, the overall risk is moderate but non-negligible. The absence of a patch increases exposure duration, necessitating proactive mitigation. Additionally, attackers could use this vulnerability as a foothold for more complex multi-stage attacks, especially in environments where Dify is integrated with other critical systems.

CWE-79Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') (opens in a new tab)
Base weaknessLikelihood of exploit: HighCWE Top 25 (2025): #1OWASP Top 10 A05:2025: Injection (opens in a new tab)
The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users.
Architecture and Design · Libraries or Frameworks
Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.
Implementation · Architecture and Design
Understand the context in which your data will be used and the encoding that will be expected. This is especially important when transmitting data between different components, or when generating outputs that can contain multiple encodings at the same time, such as web pages or multi-part mail messages.
Architecture and Design · Implementation · Attack Surface Reduction
Understand all the potential areas where untrusted inputs can enter your software: parameters or arguments, cookies, anything read from the network, environment variables, reverse DNS lookups, query results, request headers, URL components, e-mail, files, filenames, databases, and any external systems that provide…
OWASP Cheat Sheets
Cross Site Scripting Prevention (opens in a new tab)
DOM based XSS Prevention (opens in a new tab)
Injection Prevention (opens in a new tab)
Abuse Case (opens in a new tab)
Deserialization (opens in a new tab)
OWASP ASVS 4.0.3
V5.3.3 (opens in a new tab)
V1.5.1 (opens in a new tab)
Attack patterns
XSS Using MIME Type Mismatch (opens in a new tab)
DOM-Based XSS (opens in a new tab)
Reflected XSS (opens in a new tab)
Stored XSS (opens in a new tab)
Cross-Site Scripting (XSS) (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

github.com/langgenius/dify/security/advisories/GHSA-grmh-ww4v-5cgj (opens in a new tab)

Community reviews

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 17 Jun 2025, 23:04 UTC

WeaknessesCWE-79

Technical details

References

Community reviews

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