A borrowed knife

A borrowed knife
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China used India-Pak conflict as ‘Live Lab’, says Dy Army Chief Rahul Singh

New Delhi: China used Pakistan to cause pain to India, and it was providing all possible support to its all-weather ally during the four-day conflict between Indian and Pakistani militaries in May, Deputy Chief of Army Staff Lt Gen Rahul R Singh said on Friday. In an address at industry chamber FICCI, the senior official said China also used the India-Pakistan conflict like a “Live Lab” available to test various weapon systems.

Lt Gen Singh also highlighted China’s ancient military strategy of “36 stratagems” and killing the adversary with a “borrowed knife” to buttress the point that Beijing extended all possible support to Pakistan to harm India. India was actually dealing with three adversaries, he said, suggesting that besides Pakistan and China, Turkiye was also playing a major role in supplying military hardware to Islamabad. The Deputy Chief of Army Staff, who looks after the Indian Army’s capability development and sustenance vertical, said Beijing’s support to Islamabad was not surprising as 81% of the military hardware of the Pakistani armed forces are from China.

“He (China) would rather use the neighbour to cause pain (to India) than getting involved in a mudslinging match on the northern border,” Lt Gen Singh said. “Pakistan was the front face. We had China providing all possible support. And there was no surprise because, if you look at the statistics in the last five years, 81 per cent of the military hardware that Pakistan is getting is all Chinese,” he said. Lt Gen Singh said Turkiye also played an important role in providing support to Pakistan. “We saw numerous drones coming and landing in the face of war, during the war, along with the individuals who were there,” he said.

The Deputy Chief of Army Staff said the “strategic messaging” by the Indian leadership was unambiguous, adding that the planning and selection of targets in Pakistan and Pakistan-occupied Kashmir (PoK) was based on a lot of data.

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