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Vyper has a double eval in For List Iter

Low severity GitHub Reviewed Published Feb 21, 2025 in vyperlang/vyper • Updated Feb 24, 2025

Package

pip vyper (pip)

Affected versions

<= 0.4.0

Patched versions

0.4.1

Description

Multiple evaluation of a single expression is possible in the iterator target of a for loop. While the iterator expression cannot produce multiple writes, it can consume side effects produced in the loop body (e.g. read a storage variable updated in the loop body) and thus lead to unexpected program behavior. Specifically, reads in iterators which contain an ifexp (e.g. for s: uint256 in ([read(), read()] if True else [])) may interleave reads with writes in the loop body.

The fix is tracked in vyperlang/vyper#4488.

Vulnerability Details

Vyper for loops allow two kinds of iterator targets, namely the range() builtin and an iterable type, like SArray and DArray.

During codegen, iterable lists are required to not produce any side-effects (in the following code, range_scope forces iter_list to be parsed in a constant context, which is checked against is_constant).

def _parse_For_list(self):
    with self.context.range_scope():
        iter_list = Expr(self.stmt.iter, self.context).ir_node
    ...

def range_scope(self):
    prev_value = self.in_range_expr
    self.in_range_expr = True
    yield
    self.in_range_expr = prev_value

def is_constant(self):
    return self.constancy is Constancy.Constant or self.in_range_expr

However, this does not prevent the iterator from consuming side effects provided by the body of the loop. For dynamic arrays, the compiler simply panics:

x: DynArray[uint256, 3]

@external
def test():
    for i: uint256 in (self.usesideeffect() if True else self.usesideeffect()):
        pass

@view
def usesideeffect() -> DynArray[uint256, 3]:
    return self.x

For SArrays on the other hand, iter_list is instantiated in the body of a repeat ir, so it can be evaluated several times.

Here are three illustrating examples. In the first example, the following test case pre-evaluates the iter list and stores the result to a temporary list in memory. So the list is only evaluated once, before entry into the loop body, and the log output will be 0, 0, 0.

event I:
    i: uint256

x: uint256

@deploy
def __init__():
    self.x = 0

@external
def test():
    for i: uint256 in [self.usesideeffect(), self.usesideeffect(), self.usesideeffect()]:
        self.x += 1
        log I(i)

@view
def usesideeffect() -> uint256:
    return self.x

However, in the next two examples, because the iterator target is not a list literal, it will be evaluated in the loop body. In the second example, iter_list is an ifexp, thus it will be evaluated lazily in the loop body. The log output will be 0, 1, 2 due to consumption of side effects.

event I:
    i: uint256

x: uint256

@deploy
def __init__():
    self.x = 0

@external
def test():
    for i: uint256 in ([self.usesideeffect(), self.usesideeffect(), self.usesideeffect()] if True else self.otherclause()):
        self.x += 1
        log I(i)

@view
def usesideeffect() -> uint256:
    return self.x

@view
def otherclause() -> uint256[3]:
    return [0, 0, 0]

In the third example, iter_list is also an ifexp, thus it will only be evaluated in the loop body. The log output will be 0, 1, 2 due to consumption of side effects.

event I:
    i: uint256

x: uint256[3]

@deploy
def __init__():
    self.x = [0, 0, 0]

@external
def test():
    for i: uint256 in (self.usesideeffect() if True else self.otherclause()):
        self.x[0] += 1
        self.x[1] += 1
        self.x[2] += 1
        log I(i)

@view
def usesideeffect() -> uint256[3]:
    return self.x

@view
def otherclause() -> uint256[3]:
    return [0, 0, 0]

References

@charles-cooper charles-cooper published to vyperlang/vyper Feb 21, 2025
Published by the National Vulnerability Database Feb 21, 2025
Published to the GitHub Advisory Database Feb 21, 2025
Reviewed Feb 21, 2025
Last updated Feb 24, 2025

Severity

Low

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements Present
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality Low
Integrity Low
Availability None
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:P/PR:L/UI:N/VC:L/VI:L/VA:N/SC:N/SI:N/SA:N

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(12th percentile)

Weaknesses

CVE ID

CVE-2025-27104

GHSA ID

GHSA-h33q-mhmp-8p67

Source code

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