GHSA-7gcp-2gmq-w3xh CVE-2017-0899

RubyGems Code Injection vulnerability

Critical RubyGems

Severity: 9.8 / 10; Critical · CVSS 3.0
Exploit chance (EPSS): 11.10%; Chance of exploitation in the next 30 days. Higher than 95.93% of scored vulnerabilities.
Known exploited: No; Not in CISA's catalog
Weakness: CWE-150 Improper Neutralization of Escape, Meta, or Control Sequences; CWE-94 Improper Control of Generation of Code ('Code Injection')
Fix: 2.6.13; Upgrade rubygems-update to this version or later

Description

RubyGems prior to 2.6.13 is vulnerable to maliciously crafted gem specifications that include terminal escape characters. Printing the gem specification would execute terminal escape sequences.

Affected versions

RubyGems

Package	Vulnerable	Fixed in
rubygems-update	`< 2.6.13`	`2.6.13`

How to fix

Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.

rubygems-update RubyGems → `2.6.13`

bundler

bundle update rubygems-update # Gemfile: gem "rubygems-update", ">= 2.6.13"

Severity breakdown

CVSS 3.0 9.8

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

Attack vector: Network
Attack complexity: Low
Privileges required: None
User interaction: None
Scope: Unchanged
Confidentiality: High
Integrity: High
Availability: High

Weakness

CWE-150: Improper Neutralization of Escape, Meta, or Control Sequences

The product receives input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could be interpreted as escape, meta, or control character sequences when they are sent to a downstream component.

How to prevent it

Developers should anticipate that escape, meta and control characters/sequences will be injected/removed/manipulated in the input vectors of their product. Use an appropriate combination of denylists and allowlists to ensure only valid, expected and appropriate input is processed by the system.
Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
Implementation: While it is risky to use dynamically-generated query strings, code, or commands that mix control and data together, sometimes it may be unavoidable. Properly quote arguments and escape any special characters within those arguments. The most conservative approach is to escape or filter all characters that do not pass an extremely strict allowlist (such as everything that is not alphanumeric or white space). If some special characters are still needed, such as white space, wrap each argument in quotes after the escaping/filtering step. Be careful of argument injection (CWE-88).
Implementation: Inputs should be decoded and canonicalized to the application's current internal representation before being validated (CWE-180). Make sure that the application does not decode the same input twice (CWE-174). Such errors could be used to bypass allowlist validation schemes by introducing dangerous inputs after they have been checked.
Implementation: When using output from an LLM, neutralize or strip escape codes before redirecting output to the terminal or other rendering engine that would process the codes. The neutralization could require that the character be printable and/or allowable whitespace, such as a carriage return or newline. Be deliberate about what to allow.
Build and Compilation: When using an LLM: during tokenizer training, suppress escape codes from the tokenizer's vocabulary. Depending on context, this could be accomplished by removing the codes from input to the tokenizer, or removing the map from the string to its token ID. It is generally unlikely that this removal would adversely affect the quality or correctness of what is generated, e.g. advice requests for terminal settings to change colors.

CWE-94: Improper Control of Generation of Code ('Code Injection')

The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.

How to prevent it

Architecture and Design: Refactor your program so that you do not have to dynamically generate code.
Architecture and Design: Run your code in a "jail" or similar sandbox environment that enforces strict boundaries between the process and the operating system. This may effectively restrict which code can be executed by your product. Examples include the Unix chroot jail and AppArmor. In general, managed code may provide some protection. This may not be a feasible solution, and it only limits the impact to the operating system; the rest of your application may still be subject to compromise. Be careful to avoid CWE-243 and other weaknesses related to jails.
Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright. To reduce the likelihood of code injection, use stringent allowlists that limit which constructs are allowed. If you are dynamically constructing code that invokes a function, then verifying that the input is alphanumeric might be insufficient. An attacker might still be able to reference a dangerous function that you did not intend to allow, such as system(), exec(), or exit().
Testing: Use dynamic tools and techniques that interact with the product using large test suites with many diverse inputs, such as fuzz testing (fuzzing), robustness testing, and fault injection. The product's operation may slow down, but it should not become unstable, crash, or generate incorrect results.
Operation: Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
Operation: Run the code in an environment that performs automatic taint propagation and prevents any command execution that uses tainted variables, such as Perl's "-T" switch. This will force the program to perform validation steps that remove the taint, although you must be careful to correctly validate your inputs so that you do not accidentally mark dangerous inputs as untainted (see CWE-183 and CWE-184).
Implementation: For Python programs, it is frequently encouraged to use the ast.literal_eval() function instead of eval, since it is intentionally designed to avoid executing code. However, an adversary could still cause excessive memory or stack consumption via deeply nested structures [REF-1372], so the python documentation discourages use of ast.literal_eval() on untrusted data [REF-1373].

References

Advisories

nvd.nist.gov/vuln/detail/CVE-2017-0899

Packages

github.com/rubygems/rubygems

Timeline

May 13, 2022 Published
Nov 8, 2023 Last updated by the source
Nov 1, 2026 Latest EPSS score

Advisory	Severity	Why it's related
GHSA-228f-g3h7-3fj3 RubyGems HTTPS to HTTP redirect	Medium	Also affects rubygems-update
GHSA-5mgj-mvv8-46mw RubyGems does not verify SSL certificate	Medium	Also affects rubygems-update
GHSA-qv62-xfj6-32xm RubyGems Improper Input Validation vulnerability	Medium	Also affects rubygems-update
GHSA-9qvm-2vhf-q649 RubyGems Regular Expression Denial of Service	Medium	Also affects rubygems-update
GHSA-8qxg-mff5-j3wc RubyGems Path Traversal vulnerability	Medium	Also affects rubygems-update
GHSA-wp3j-rvfp-624h RubyGems vulnerable to DNS hijack attack	High	Also affects rubygems-update
GHSA-9j7m-rjqx-48vh RubyGems Regular Expression Denial of Service vulnerability	Medium	Also affects rubygems-update
GHSA-p7f2-rr42-m9xm RubyGems Improper Input Validation vulnerability	High	Also affects rubygems-update

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