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Common Weakness Enumeration

A community-developed list of SW & HW weaknesses that can become vulnerabilities

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Home > CWE List > CWE- Individual Dictionary Definition (4.15)  
ID

CWE-1300: Improper Protection of Physical Side Channels

Weakness ID: 1300
Vulnerability Mapping: ALLOWEDThis CWE ID may be used to map to real-world vulnerabilities
Abstraction: BaseBase - a weakness that is still mostly independent of a resource or technology, but with sufficient details to provide specific methods for detection and prevention. Base level weaknesses typically describe issues in terms of 2 or 3 of the following dimensions: behavior, property, technology, language, and resource.
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+ Description
The device does not contain sufficient protection mechanisms to prevent physical side channels from exposing sensitive information due to patterns in physically observable phenomena such as variations in power consumption, electromagnetic emissions (EME), or acoustic emissions.
+ Extended Description

An adversary could monitor and measure physical phenomena to detect patterns and make inferences, even if it is not possible to extract the information in the digital domain.

Physical side channels have been well-studied for decades in the context of breaking implementations of cryptographic algorithms or other attacks against security features. These side channels may be easily observed by an adversary with physical access to the device, or using a tool that is in close proximity. If the adversary can monitor hardware operation and correlate its data processing with power, EME, and acoustic measurements, the adversary might be able to recover of secret keys and data.

+ Common Consequences
Section HelpThis table specifies different individual consequences associated with the weakness. The Scope identifies the application security area that is violated, while the Impact describes the negative technical impact that arises if an adversary succeeds in exploiting this weakness. The Likelihood provides information about how likely the specific consequence is expected to be seen relative to the other consequences in the list. For example, there may be high likelihood that a weakness will be exploited to achieve a certain impact, but a low likelihood that it will be exploited to achieve a different impact.
ScopeImpactLikelihood
Confidentiality

Technical Impact: Read Memory; Read Application Data

+ Potential Mitigations

Phase: Architecture and Design

Apply blinding or masking techniques to implementations of cryptographic algorithms.

Phase: Implementation

Add shielding or tamper-resistant protections to the device to increase the difficulty of obtaining measurements of the side-channel.
+ Relationships
Section HelpThis table shows the weaknesses and high level categories that are related to this weakness. These relationships are defined as ChildOf, ParentOf, MemberOf and give insight to similar items that may exist at higher and lower levels of abstraction. In addition, relationships such as PeerOf and CanAlsoBe are defined to show similar weaknesses that the user may want to explore.
+ Relevant to the view "Research Concepts" (CWE-1000)
NatureTypeIDName
ChildOfBaseBase - a weakness that is still mostly independent of a resource or technology, but with sufficient details to provide specific methods for detection and prevention. Base level weaknesses typically describe issues in terms of 2 or 3 of the following dimensions: behavior, property, technology, language, and resource.203Observable Discrepancy
ParentOfVariantVariant - a weakness that is linked to a certain type of product, typically involving a specific language or technology. More specific than a Base weakness. Variant level weaknesses typically describe issues in terms of 3 to 5 of the following dimensions: behavior, property, technology, language, and resource.1255Comparison Logic is Vulnerable to Power Side-Channel Attacks
Section HelpThis table shows the weaknesses and high level categories that are related to this weakness. These relationships are defined as ChildOf, ParentOf, MemberOf and give insight to similar items that may exist at higher and lower levels of abstraction. In addition, relationships such as PeerOf and CanAlsoBe are defined to show similar weaknesses that the user may want to explore.
+ Relevant to the view "Hardware Design" (CWE-1194)
NatureTypeIDName
MemberOfCategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic.1388Physical Access Issues and Concerns
ChildOfBaseBase - a weakness that is still mostly independent of a resource or technology, but with sufficient details to provide specific methods for detection and prevention. Base level weaknesses typically describe issues in terms of 2 or 3 of the following dimensions: behavior, property, technology, language, and resource.203Observable Discrepancy
+ Modes Of Introduction
Section HelpThe different Modes of Introduction provide information about how and when this weakness may be introduced. The Phase identifies a point in the life cycle at which introduction may occur, while the Note provides a typical scenario related to introduction during the given phase.
PhaseNote
Implementation
+ Applicable Platforms
Section HelpThis listing shows possible areas for which the given weakness could appear. These may be for specific named Languages, Operating Systems, Architectures, Paradigms, Technologies, or a class of such platforms. The platform is listed along with how frequently the given weakness appears for that instance.

Languages

Class: Not Language-Specific (Undetermined Prevalence)

Operating Systems

Class: Not OS-Specific (Undetermined Prevalence)

Architectures

Class: Not Architecture-Specific (Undetermined Prevalence)

Technologies

Class: Not Technology-Specific (Undetermined Prevalence)

+ Demonstrative Examples

Example 1

Consider a device that checks a passcode to unlock the screen.

(bad code)
 
As each character of the PIN number is entered, a correct character exhibits one current pulse shape while an incorrect character exhibits a different current pulse shape.

PIN numbers used to unlock a cell phone should not exhibit any characteristics about themselves. This creates a side channel. An attacker could monitor the pulses using an oscilloscope or other method. Once the first character is correctly guessed (based on the oscilloscope readings), they can then move to the next character, which is much more efficient than the brute force method of guessing every possible sequence of characters.

(good code)
 
Rather than comparing each character to the correct PIN value as it is entered, the device could accumulate the PIN in a register, and do the comparison all at once at the end. Alternatively, the components for the comparison could be modified so that the current pulse shape is the same regardless of the correctness of the entered character.

Example 2

Consider the device vulnerability CVE-2021-3011, which affects certain microcontrollers [REF-1221]. The Google Titan Security Key is used for two-factor authentication using cryptographic algorithms. The device uses an internal secret key for this purpose and exchanges information based on this key for the authentication. If this internal secret key and the encryption algorithm were known to an adversary, the key function could be duplicated, allowing the adversary to masquerade as the legitimate user.

(bad code)
 
The local method of extracting the secret key consists of plugging the key into a USB port and using electromagnetic (EM) sniffing tools and computers.
(good code)
 
Several solutions could have been considered by the manufacturer. For example, the manufacturer could shield the circuitry in the key or add randomized delays, indirect calculations with random values involved, or randomly ordered calculations to make extraction much more difficult or a combination of these techniques.

Example 3

The code snippet provided here is part of the modular exponentiation module found in the HACK@DAC'21 Openpiton System-on-Chip (SoC), specifically within the RSA peripheral [REF-1368]. Modular exponentiation, denoted as "a^b mod n," is a crucial operation in the RSA public/private key encryption. In RSA encryption, where 'c' represents ciphertext, 'm' stands for a message, and 'd' corresponds to the private key, the decryption process is carried out using this modular exponentiation as follows: m = c^d mod n, where 'n' is the result of multiplying two large prime numbers.

(bad code)
Example Language: Verilog 
...
module mod_exp
...
`UPDATE: begin
if (exponent_reg != 'd0) begin
if (exponent_reg[0])
result_reg <= result_next;
base_reg <= base_next;
exponent_reg <= exponent_next;
state <= `UPDATE;
...
endmodule

The vulnerable code shows a buggy implementation of binary exponentiation where it updates the result register (result_reg) only when the corresponding exponent bit (exponent_reg[0]) is set to 1. However, when this exponent bit is 0, the output register is not updated. It's important to note that this implementation introduces a physical power side-channel vulnerability within the RSA core. This vulnerability could expose the private exponent to a determined physical attacker. Such exposure of the private exponent could lead to a complete compromise of the private key.

To address mitigation requirements, the developer can develop the module by minimizing dependency on conditions, particularly those reliant on secret keys. In situations where branching is unavoidable, developers can implement masking mechanisms to obfuscate the power consumption patterns exhibited by the module (see good code example). Additionally, certain algorithms, such as the Karatsuba algorithm, can be implemented as illustrative examples of side-channel resistant algorithms, as they necessitate only a limited number of branch conditions [REF-1369].

(good code)
Example Language: Verilog 
...
module mod_exp
...
`UPDATE: begin
if (exponent_reg != 'd0) begin
if (exponent_reg[0]) begin
result_reg <= result_next;
end else begin
mask_reg <= result_next;
end
base_reg <= base_next;
exponent_reg <= exponent_next;
state <= `UPDATE;
...
endmodule

+ Observed Examples
ReferenceDescription
Power side-channels leak secret information from processor
electromagnetic-wave side-channel in security-related microcontrollers allows extraction of private key
Crypto hardware wallet's power consumption relates to total number of pixels illuminated, creating a side channel in the USB connection that allows attackers to determine secrets displayed such as PIN numbers and passwords
Chain: microcontroller system-on-chip contains uses a register value stored in flash to set product protection state on the memory bus but does not contain protection against fault injection (CWE-1319), which leads to an incorrect initialization of the memory bus (CWE-1419) leading the product to be in an unprotected state.
message encryption software uses certain instruction sequences that allows RSA key extraction using a chosen-ciphertext attack and acoustic cryptanalysis
virtualization product allows recovery of AES keys from the guest OS using a side channel attack against a power/energy monitoring interface.
power consumption varies based on number of pixels being illuminated in a display, allowing reading of secrets such as the PIN by using the USB interface to measure power consumption
+ Weakness Ordinalities
OrdinalityDescription
Primary
(where the weakness exists independent of other weaknesses)
Resultant
(where the weakness is typically related to the presence of some other weaknesses)
+ Detection Methods

Manual Analysis

Perform a set of leakage detection tests such as the procedure outlined in the Test Vector Leakage Assessment (TVLA) test requirements for AES [REF-1230]. TVLA is the basis for the ISO standard 17825 [REF-1229]. A separate methodology is provided by [REF-1228]. Note that sole reliance on this method might not yield expected results [REF-1239] [REF-1240].

Effectiveness: Moderate

Manual Analysis

Post-silicon, perform full side-channel attacks (penetration testing) covering as many known leakage models as possible against test code.

Effectiveness: Moderate

Manual Analysis

Pre-silicon - while the aforementioned TVLA methods can be performed post-silicon, models of device power consumption or other physical emanations can be built from information present at various stages of the hardware design process before fabrication. TVLA or known side-channel attacks can be applied to these simulated traces and countermeasures applied before tape-out. Academic research in this field includes [REF-1231] [REF-1232] [REF-1233].

Effectiveness: Moderate

+ Functional Areas
  • Power
+ Memberships
Section HelpThis MemberOf Relationships table shows additional CWE Categories and Views that reference this weakness as a member. This information is often useful in understanding where a weakness fits within the context of external information sources.
NatureTypeIDName
MemberOfViewView - a subset of CWE entries that provides a way of examining CWE content. The two main view structures are Slices (flat lists) and Graphs (containing relationships between entries).1343Weaknesses in the 2021 CWE Most Important Hardware Weaknesses List
MemberOfCategoryCategory - a CWE entry that contains a set of other entries that share a common characteristic.1417Comprehensive Categorization: Sensitive Information Exposure
+ Vulnerability Mapping Notes

Usage: ALLOWED

(this CWE ID could be used to map to real-world vulnerabilities)

Reason: Acceptable-Use

Rationale:

This CWE entry is at the Base level of abstraction, which is a preferred level of abstraction for mapping to the root causes of vulnerabilities.

Comments:

Carefully read both the name and description to ensure that this mapping is an appropriate fit. Do not try to 'force' a mapping to a lower-level Base/Variant simply to comply with this preferred level of abstraction.
+ References
[REF-1117] Paul Kocher, Joshua Jaffe and Benjamin Jun. "Introduction to differential power analysis and related attacks". 1998. <https://www.rambus.com/wp-content/uploads/2015/08/DPATechInfo.pdf>.
[REF-1118] Dakshi Agrawal, Bruce Archambeault, Josyula R. Rao and Pankaj Rohatgi. "The EM Side-Channel(s)". 2007-08-24. <https://link.springer.com/content/pdf/10.1007/3-540-36400-5_4.pdf>. URL validated: 2023-04-07.
[REF-1119] Daniel Genkin, Adi Shamir and Eran Tromer. "RSA key extraction via low-bandwidth acoustic cryptanalysis". 2014-06-13. <https://www.iacr.org/archive/crypto2014/86160149/86160149.pdf>.
[REF-1120] Colin O'Flynn. "Power Analysis for Cheapskates". 2013-01-24. <https://media.blackhat.com/eu-13/briefings/OFlynn/bh-eu-13-for-cheapstakes-oflynn-wp.pdf>.
[REF-1055] Peter Gutmann. "Data Remanence in Semiconductor Devices". 10th USENIX Security Symposium. 2001-08. <https://www.usenix.org/legacy/events/sec01/full_papers/gutmann/gutmann.pdf>.
[REF-1218] Graham Cluley. "This Black Box Can Brute Force Crack iPhone PIN Passcodes". The Mac Security Blog. 2015-03-16. <https://www.intego.com/mac-security-blog/iphone-pin-pass-code/>.
[REF-1221] Victor Lomne and Thomas Roche. "A Side Journey to Titan". 2021-01-07. <https://web.archive.org/web/20210107182441/https://ninjalab.io/wp-content/uploads/2021/01/a_side_journey_to_titan.pdf>. URL validated: 2023-04-07.
[REF-1228] Gilbert Goodwill, Benjamin Jun, Josh Jaffe and Pankaj Rohatgi. "A testing methodology for side-channel resistance validation". 2011. <https://csrc.nist.gov/csrc/media/events/non-invasive-attack-testing-workshop/documents/08_goodwill.pdf>.
[REF-1229] ISO/IEC. "ISO/IEC 17825:2016: Testing methods for the mitigation of non-invasive attack classes against cryptographic modules". 2016. <https://www.iso.org/standard/60612.html>.
[REF-1230] Cryptography Research Inc.. "Test Vector Leakage Assessment (TVLA) Derived Test Requirements (DTR) with AES". 2015-08. <https://www.rambus.com/wp-content/uploads/2015/08/TVLA-DTR-with-AES.pdf>.
[REF-1231] Danilo Šijaˇci´, Josep Balasch, Bohan Yang, Santosh Ghosh and Ingrid Verbauwhede. "Towards efficient and automated side-channel evaluations at design time". pp. 305-319. Journal of Cryptographic Engineering, 10(4). 2020. <https://www.esat.kuleuven.be/cosic/publications/article-3204.pdf>.
[REF-1232] Amit Kumar, Cody Scarborough, Ali Yilmaz and Michael Orshansky. "Efficient simulation of EM side-channel attack resilience". pp. 123-130. IEEE/ACM International Conference on Computer-Aided Design (ICCAD). 2017. <https://dl.acm.org/doi/pdf/10.5555/3199700.3199717>. URL validated: 2023-04-07.
[REF-1233] Yuan Yao, Tuna Tufan, Tarun Kathuria, Baris Ege, Ulkuhan Guler and Patrick Schaumont. "Pre-silicon Architecture Correlation Analysis (PACA): Identifying and Mitigating the Source of Side-channel Leakage at Gate-level". IACR Cryptology ePrint Archive. 2021-04-21. <https://eprint.iacr.org/2021/530.pdf>.
[REF-1234] Elisabeth Oswald, Thomas Popp and Stefan Mangard. "Power Analysis Attacks - Revealing the Secrets of Smart Cards". 2007. <https://link.springer.com/book/10.1007/978-0-387-38162-6>. URL validated: 2023-04-07.
[REF-1235] David Oswald, Bastian Richter and Christof Paar. "Side-Channel Attacks on the Yubikey 2 One-Time Password Generator". 2013-06-14. <https://www.emsec.ruhr-uni-bochum.de/media/crypto/veroeffentlichungen/2014/02/04/paper_yubikey_sca.pdf>.
[REF-1239] François-Xavier Standaert. "How (not) to Use Welch's T-test in Side-Channel Security Evaluations". IACR Cryptology ePrint Archive. 2017-02-15. <https://eprint.iacr.org/2017/138.pdf>.
[REF-1240] Carolyn Whitnall and Elisabeth Oswald. "A Critical Analysis of ISO 17825 ('Testing methods for the mitigation of non-invasive attack classes against cryptographic modules')". IACR Cryptology ePrint Archive. 2019-09-10. <https://eprint.iacr.org/2019/1013.pdf>.
[REF-1285] Texas Instruments. "Physical Security Attacks Against Silicon Devices". 2022-01-31. <https://www.ti.com/lit/an/swra739/swra739.pdf?ts=1644234570420>.
[REF-1286] Lennert Wouters, Benedikt Gierlichs and Bart Preneel. "On The Susceptibility of Texas Instruments SimpleLink Platform Microcontrollers to Non-Invasive Physical Attacks". 1.2 / 5. 2022-03-14. <https://eprint.iacr.org/2022/328.pdf>.
+ Content History
+ Submissions
Submission DateSubmitterOrganization
2020-05-29
(CWE 4.2, 2020-08-20)
Nicole FernTortuga Logic
+ Contributions
Contribution DateContributorOrganization
2021-10-11Anders Nordstrom, Alric AlthoffTortuga Logic
Provided detection methods, observed examples, and references
2021-10-13Nicole FernRiscure
Provided detection methods, observed examples, and references
2023-06-21Chen Chen, Rahul Kande, Jeyavijayan RajendranTexas A&M University
suggested demonstrative example
2023-06-21Shaza Zeitouni, Mohamadreza Rostami, Ahmad-Reza SadeghiTechnical University of Darmstadt
suggested demonstrative example
+ Modifications
Modification DateModifierOrganization
2021-03-15CWE Content TeamMITRE
updated Functional_Areas, Maintenance_Notes
2021-07-20CWE Content TeamMITRE
updated Related_Attack_Patterns
2021-10-28CWE Content TeamMITRE
updated Demonstrative_Examples, Description, Detection_Factors, Maintenance_Notes, Name, Observed_Examples, References, Relationships, Weakness_Ordinalities
2022-06-28CWE Content TeamMITRE
updated Relationships
2022-10-13CWE Content TeamMITRE
updated References, Relationships
2023-01-31CWE Content TeamMITRE
updated Related_Attack_Patterns
2023-04-27CWE Content TeamMITRE
updated References, Relationships
2023-06-29CWE Content TeamMITRE
updated Mapping_Notes
2023-10-26CWE Content TeamMITRE
updated Demonstrative_Examples, Observed_Examples, References
+ Previous Entry Names
Change DatePrevious Entry Name
2021-10-28Improper Protection Against Physical Side Channels
Page Last Updated: July 16, 2024