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([2405:6e00:634:7891:2b45:7371:96b8:aba1]) by smtp.gmail.com with ESMTPSA id d2e1a72fcca58-82f67411135sm804502b3a.42.2026.04.14.22.41.01 (version=TLS1_3 cipher=TLS_AES_128_GCM_SHA256 bits=128/128); Tue, 14 Apr 2026 22:41:09 -0700 (PDT) Message-ID: Date: Wed, 15 Apr 2026 15:40:58 +1000 Precedence: bulk X-Mailing-List: netdev@vger.kernel.org List-Id: List-Subscribe: List-Unsubscribe: MIME-Version: 1.0 User-Agent: Mozilla Thunderbird Subject: Re: [RFC net-next 1/3] net/tls_sw: support randomized zero padding To: Alistair Francis , Wilfred Mallawa , "kuba@kernel.org" Cc: "corbet@lwn.net" , "dlemoal@kernel.org" , "davem@davemloft.net" , "linux-kselftest@vger.kernel.org" , "john.fastabend@gmail.com" , "sd@queasysnail.net" , "linux-kernel@vger.kernel.org" , "linux-doc@vger.kernel.org" , "pabeni@redhat.com" , "skhan@linuxfoundation.org" , "edumazet@google.com" , "horms@kernel.org" , "netdev@vger.kernel.org" References: <20260309054837.2299732-2-wilfred.opensource@gmail.com> <20260309054837.2299732-3-wilfred.opensource@gmail.com> <20260314073919.2f92b966@kernel.org> <9e9f6eb89ba95e9fbb764e2807420e98b566bf37.camel@wdc.com> <20260316180355.37d45785@kernel.org> <8f29d43fc1fd7e6feec4c24131eb2c0292a8c0fd.camel@wdc.com> <20260316183023.2fb38d84@kernel.org> <64cb821cc09226155059807cb0bcdbc51ae8d0d6.camel@wdc.com> <49513ee4347536e7c8419e9e65b8c619a8c665bb.camel@wdc.com> Content-Language: en-US, en-ZM From: Wilfred Mallawa In-Reply-To: <49513ee4347536e7c8419e9e65b8c619a8c665bb.camel@wdc.com> Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 7bit >>> Sorry, I realized when i hit "send" that I phrased my previous >>> message >>> poorly. When I say "potential" I mean someone actually presenting a >>> PoC >>> and a CVE is issued for it. Have we seen any of those? > In 2014 a group at UC Berkeley used HTTPS traffic analysis to identify: > > "individual pages in the same web-site with 90% accuracy, exposing > personal details including medical conditions, financial and legal > affairs and sexual orientation." > > They used machine learning to help and that was over 10 years ago. So I > suspect modern day machine learning would make this even easier to do > today. > > Obviously that is HTTP traffic, which is different to the NVMe-TCP > traffic this series is targeting, but it does still seem like a real > concern. > > They talk about a range of defences in the paper, with tradeoffs > between all of them. But the linear defence seems like the one that is > applicable here: > > "linear defense pads all packet sizes up to multiples of 128" > > The linear defence seems to reduce the Pan attack from 60% to around > 25% and the BoG attack from 90% to around 60%. > > On top of that the > > "Burst defense offers greater protection, operating between the TCP > layer and application layer to pad contiguous bursts of traffic up to > predefined thresholds uniquely determined for each website" > > Which to me sounds like the random padding proposed in this series > would provide more protection then the basic linear padding used in the > paper. > > To me analysing TLS traffic does seem like a plausible threat and > something that randomised padding would help with. Leaving it up to > userspace to decide based on their threat model seems like a good > approach as well. > > 1: https://secml.cs.berkeley.edu/pets2014/ > > Alistair gentle ping. Are there any further thoughts on adding this support? Wilfred